1487 Matplotlib Jobs - Page 44

Join us as a "Chief Control Office" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences. You may be assessed on the key critical skills relevant for success in role, such as experience with MS office, SQL, Alteryx, Power Tools, Python as well as job-specific skillsets. To be successful as an "Analyst", you should have experience with: Basic/ Essential Qualifications Graduate in any discipline Experience in Controls, Governance, Reporting and Risk Management preferably in a financial services organisation Proficient in MS Office – PPT, Excel, Work & Visio Proficient in SQL, Alteryx and Python Generating Data Insights and Dashboards from large and diverse data sets Excellent experience on Tableau, Alteryx, MS Office (i.e. Advance Excel, PowerPoint) Automation skills using VBA, PowerQuery, PowerApps, etc. Experience in using ETL tools. Good understanding of Risk and Control Excellent communication skills (Verbal and Written) Good understanding of governance and control frameworks and processes Highly motivated, business-focussed and forward thinking. Experience in senior stakeholder management. Ability to manage relationships across multiple disciplines Desirable Skillsets/ Good To Have Experience in data crunching/ analysis including automation Experience in handling RDBMS (i.e. SQL/Oracle) Experience in Python, Data Science and Data Analytics Tools and Techniques e.g. MatPlotLib, Data Wrangling, Low Code/No Code environment development preferably in large bank on actual use cases Understanding of Data Management Principles and data governance Design and managing SharePoints Financial Services experience This role will be based out of Pune. Purpose of the role To design, develop and consult on the bank’s internal controls framework and supporting policies and standards across the organisation, ensuring it is robust, effective, and aligned to the bank’s overall strategy and risk appetite. Accountabilities Identification and analysis of emerging and evolving risks across functions to understand their potential impact, and likelihood. Communication of the purpose, structure, and importance of the control framework to all relevant stakeholders, including senior management and audit. Support to the development and implementation of the bank's internal controls framework and principles tailored to the banks specific needs and risk profile including design, monitoring, and reporting initiatives . Monitoring and maintenance of the control's frameworks, to ensure compliance and adjust and update as internal and external requirements change. Embedment of the control framework across the bank through cross collaboration, training sessions and awareness campaigns which fosters a culture of knowledge sharing and improvement in risk management and the importance of internal control effectiveness. Analyst Expectations To meet the needs of stakeholders/ customers through specialist advice and support Perform prescribed activities in a timely manner and to a high standard which will impact both the role itself and surrounding roles. Likely to have responsibility for specific processes within a team They may lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. They supervise a team, allocate work requirements and coordinate team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they manage own workload, take responsibility for the implementation of systems and processes within own work area and participate on projects broader than direct team. Execute work requirements as identified in processes and procedures, collaborating with and impacting on the work of closely related teams. Check work of colleagues within team to meet internal and stakeholder requirements. Provide specialist advice and support pertaining to own work area. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct. Maintain and continually build an understanding of how all teams in area contribute to the objectives of the broader sub-function, delivering impact on the work of collaborating teams. Continually develop awareness of the underlying principles and concepts on which the work within the area of responsibility is based, building upon administrative / operational expertise. Make judgements based on practise and previous experience. Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures. Communicate sensitive or difficult information to customers in areas related specifically to customer advice or day to day administrative requirements. Build relationships with stakeholders/ customers to identify and address their needs. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. Show more Show less

Join us as an "BA4 - Control Data Analytics and Reporting" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. To be successful as an "BA4 - Control Data Analytics and Reporting", you should have experience with: Basic/ Essential Qualifications Graduate in any discipline. Experience in Controls, Governance, Reporting and Risk Management preferably in a financial services organization. Proficient in MS Office – PPT, Excel, Work & Visio. Proficient in SQL, Tableau and Python. Generating Data Insights and Dashboards from large and diverse data sets. Excellent experience on Tableau, Alteryx, MS Office (i.e. Advance Excel, PowerPoint). Automation skills using VBA, Power Query, PowerApps, etc. Experience in using ETL tools. Good understanding of Risk and Control. Excellent communication skills (Verbal and Written). Good understanding of governance and control frameworks and processes. Highly motivated, business-focused and forward thinking. Experience in senior stakeholder management. Ability to manage relationships across multiple disciplines. Self-driven and proactively participates in team initiatives. Demonstrated initiative in identifying and resolving problems. Desirable Skillsets/ Good To Have Experience in data crunching/ analysis including automation. Experience in handling RDBMS (i.e. SQL/Oracle). Experience in Python, Data Science and Data Analytics Tools and Techniques e.g. MatPlotLib, Data Wrangling, Low Code/No Code environment development preferably in large bank on actual use cases. Understanding of Data Management Principles and data governance. Design and managing SharePoint. Financial Services experience. Location: Noida. You may be assessed on the key critical skills relevant for success in role, such as experience with MS office, MS Power Platforms, Python, Tableau as well as job-specific skillsets. Additional experience in Alteryx would be an added advantage. Purpose of the role To design, develop and consult on the bank’s internal controls framework and supporting policies and standards across the organisation, ensuring it is robust, effective, and aligned to the bank’s overall strategy and risk appetite. Accountabilities Identification and analysis of emerging and evolving risks across functions to understand their potential impact, and likelihood. Communication of the purpose, structure, and importance of the control framework to all relevant stakeholders, including senior management and audit. Support to the development and implementation of the bank's internal controls framework and principles tailored to the banks specific needs and risk profile including design, monitoring, and reporting initiatives . Monitoring and maintenance of the control's frameworks, to ensure compliance and adjust and update as internal and external requirements change. Embedment of the control framework across the bank through cross collaboration, training sessions and awareness campaigns which fosters a culture of knowledge sharing and improvement in risk management and the importance of internal control effectiveness. Analyst Expectations To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise Thorough understanding of the underlying principles and concepts within the area of expertise They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for end results of a team’s operational processing and activities. Escalate breaches of policies / procedure appropriately. Take responsibility for embedding new policies/ procedures adopted due to risk mitigation. Advise and influence decision making within own area of expertise. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct. Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Make evaluative judgements based on the analysis of factual information, paying attention to detail. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Guide and persuade team members and communicate complex / sensitive information. Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. Show more Show less

Function: Data Science Job: Machine Learning Engineer Position: Senior Immediate manager (N+1 Job title and name): AI Manager Additional reporting line to: Global VP Engineering Position location: Mumbai, Pune, Bangalore, Hyderabad, Noida. 1. Purpose of the Job – A simple statement to identify clearly the objective of the job. The Senior Machine Learning Engineer is responsible for designing, implementing, and deploying scalable and efficient machine learning algorithms to solve complex business problems. The Machine Learning Engineer is also responsible of the lifecycle of models, once deployed in production environments, through monitoring performance and model evolution. The position is highly technical and requires an ability to collaborate with multiple technical and non-technical profiles (data scientists, data engineers, data analysts, product owners, business experts), and actively take part in a large data science community. 2. Organization chart – Indicate schematically the position of the job within the organization. It is sufficient to indicate one hierarchical level above (including possible functional boss) and, if applicable, one below the position. In the horizontal direction, the other jobs reporting to the same superior should be indicated. A Machine Learning Engineer reports to the AI Manager who reports to the Global VP Engineering. 3. Key Responsibilities and Expected Deliverables– This details what actually needs to be done; the duties and expected outcomes. Managing the lifecycle of machine learning models Develop and implement machine learning models to solve complex business problems. Ensure that models are accurate, efficient, reliable, and scalable. Deploy machine learning models to production environments, ensuring that models are integrated with software systems. Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly. Maintain machine learning models over time. This includes updating models as new data becomes available, retraining models to improve performance, and retiring models that are no longer effective. Develop and implement policies and procedures for ensuring the ethical and responsible use of machine learning models. This includes addressing issues related to bias, fairness, transparency, and accountability. Development of data science assets Identify cross use cases data science needs that could be mutualised in a reusable piece of code. Design, contribute and participate in the implementation of python libraries answering a data science transversal need that can be reused in several projects. Maintain existing data science assets (timeseries forecasting asset, model monitoring asset) Create documentation and knowledge base on data science assets to ensure a good understanding from users. Participate to asset demos to showcase new features to users. Be an active member of the Sodexo Data Science Community Participate to the definition and maintenance of engineering standards and set of good practices around machine learning. Participate to data science team meeting and regularly share knowledge, ask questions, and learn from others. Mentor and guide junior machine learning engineers and data scientists. Participate to internal or external relevant conferences and meet ups. Continuous Improvements Stay up to date with the latest developments in the field: read research papers, attend conferences, and participate in trainings to expand their knowledge and skills. Identify and evaluate new technologies and tools that can improve the efficiency and effectiveness of machine learning projects. Propose and implement optimizations for current machine learning workflows and systems. Proactively identify areas of improvement within the pipelines. Make sure that created code is compliant with our set of engineering standards. Collaboration with other data experts (Data Engineers, Platform Engineers, and Data Analysts) Participate to pull requests reviews coming from other team members. Ask for review and comments when submitting their own work. Actively participate to the day-to-day life of the project (Agile rituals), the data science team (DS meeting) and the rest of the Global Engineering team 4. Education & Experience – Indicate the skills, knowledge and experience that the job holder should require to conduct the role effectively Engineering Master’s degree or PhD in Data Science, Statistics, Mathematics, or related fields 5 years+ experience in a Data Scientist / Machine Learning Engineer role into large corporate organizations Experience of working with ML models in a cloud ecosystem Statistics & Machine Learning Statistics : Strong understanding of statistical analysis and modelling techniques (e.g., regression analysis, hypothesis testing, time series analysis) Classical ML : Very strong knowledge in classical ML algorithms for regression & classification, supervised and unsupervised machine learning, both theoretical and practical (e.g. using scikit-learn, xgboost) ML niche: Expertise in at least one of the following ML specialisations: Timeseries forecasting / Natural Language Processing / Computer Vision Deep Learning: Good knowledge of Deep Learning fundamentals (CNN, RNN, transformer architecture, attention mechanism, …) and one of the deep learning frameworks (pytorch, tensorflow, keras) Generative AI: Good understanding of Generative AI specificities and previous experience in working with Large Language Models is a plus (e.g. with openai, langchain) MLOps Model strategy : Expertise in designing, implementing, and testing machine learning strategies. Model integration : Very strong skills in integrating a machine learning algorithm in a data science application in production. Model performance: Deep understanding of model performance evaluation metrics and existing libraries (e.g., scikit-learn, evidently) Model deployment: Experience in deploying and managing machine learning models in production either using specific cloud platform, model serving frameworks, or containerization. Model monitoring : Experience with model performance monitoring tools is a plus (Grafana, Prometheus) Software Engineering Python: Very strong coding skills in Python including modularity, OOP, data & config manipulation frameworks (e.g., pandas, pydantic) etc. Python ecosystem: Strong knowledge of tooling in Python ecosystem such as dependency management tooling (venv, poetry), documentation frameworks (e.g. sphinx, mkdocs, jupyter-book), testing frameworks (unittest, pytest) Software engineering practices: Experience in putting in place good software engineering practices such as design patterns, testing (unit, integration), clean code, code formatting etc. Debugging : Ability to troubleshoot and debug issues within machine learning pipelines Data Science Experimentation and Analytics Data Visualization : Knowledge of data visualization tools such as plotly, seaborn, matplotlib, etc. to visualise, interpret and communicate the results of machine learning models to stakeholders. Basic knowledge of PowerBI is a plus Data Cleaning : Experience with data cleaning and preprocessing techniques such as feature scaling, dimensionality reduction, and outlier detection (e.g. with pandas, scikit-learn). Data Science Experiments : Understanding of experimental design and A/B testing methodologies Data Processing: Databricks/Spark : Basic knowledge of PySpark for big data processing Databases : Basic knowledge of SQL to query data in internal systems Data Formats : Familiarity with different data storage formats such as Parquet and Delta DevOps Azure DevOps : Experience using a DevOps platform such as Azure DevOps for using Boards, Repositories, Pipelines Git: Experience working with code versioning (git), branch strategies, and collaborative work with pull requests. Proficient with the most basic git commands. CI / CD : Experience in implementing/maintaining pipelines for continuous integration (including execution of testing strategy) and continuous deployment is preferable. Cloud Platform: Azure Cloud : Previous experience with services like Azure Machine Learning Services and/or Azure Databricks on Azure is preferable. Soft skills Strong analytical and problem-solving skills, with attention to detail Excellent verbal and written communication and pedagogical skills with technical and non-technical teams Excellent teamwork and collaboration skills Adaptability and reactivity to new technologies, tools, and techniques Fluent in English 5. Competencies – Indicate which of the Sodexo core competencies and any professional competencies that the role requires Communication & Collaboration Adaptability & Agility Analytical & technical skills Innovation & Change Rigorous Problem Solving & Troubleshooting Show more Show less

We are seeking a passionate and dedicated machine learning intern to join our team. As an intern, you will work closely with experienced data scientists and engineers to develop, test, and deploy machine learning models. This is an excellent opportunity to gain hands-on experience with cutting-edge technologies and contribute to real-world projects. Selected Intern's Day-to-day Responsibilities Include Collaborate with the team to collect, preprocess, and analyze datasets. Develop and train machine learning models for specific use cases. Evaluate model performance using appropriate metrics and improve accuracy and efficiency. Assist in deploying ML models into production environments. Document processes, findings, and insights throughout the project lifecycle. Stay updated on the latest trends and advancements in machine learning and AI. Qualifications Currently pursuing or recently completed a degree in computer science, data science, Machine Learning, or a related field. Strong knowledge of programming languages such as Python (preferred) or R. Familiarity with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Basic understanding of supervised and unsupervised learning, NLP, or computer vision. Hands-on experience with data preprocessing and visualization libraries (e.g., Pandas, NumPy, Matplotlib). Problem-solving mindset and eagerness to learn new technologies. Preferred Skills Experience with SQL and working with databases. Knowledge of cloud platforms like AWS, Google Cloud, or Azure. Understanding of version control systems (e.g., Git). About Company: LineupX is a B2B company that streamlines talent acquisition in just 4 easy steps. Our solution integrates human and machine intelligence to deliver an unparalleled experience for organizations and individuals alike. The industry we aim to revolutionize is currently valued at $400 billion globally. LineupX utilizes technology-driven recruitment solutions, employing machine learning and human expertise to redefine global talent acquisition practices. LineupX is an early-stage startup with promising traction, supported by angel investments, and generating revenue. We have been recognized by SINE IIT Bombay as a high-potential startup and endorsed by Canqbate50, a Canada-based startup program aimed at identifying and funding the top 50 startups from India to establish operations in Canada. Show more Show less

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. What Primary Responsibilities: Business Knowledge: Capable of understanding the requirements for the entire project (not just own features) Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them. Design: Can design and implement machine learning models and algorithms Can articulate and evaluate pros/cons of different AI/ML approaches Can generate cost estimates for model training and deployment Coding/Testing: Builds and optimizes machine learning pipelines Knows & brings in external ML frameworks and libraries Consistently avoids common pitfalls in model development and deployment How Quality: Solves cross-functional problems using data-driven approaches Identifies impacts/side effects of models outside of immediate scope of work Identifies cross-module issues related to data integration and model performance Identifies problems predictively using data analysis Productivity: Capable of working on multiple AI/ML projects simultaneously and context switching between them Process: Enforces process standards for model development and deployment. Independence: Acts independently to determine methods and procedures on new or special assignments Prioritizes large tasks and projects effectively Agility: Release Planning: Works with the PO to do high-level release commitment and estimation Works with PO on defining stories of appropriate size for model development Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration Shows Agile leadership qualities and leads by example WITH Team Work: Capable of working with development teams and identifying the right division of technical responsibility based on skill sets. Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs Initiative: Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution Capable of thinking outside-the-box to view the system as it should be rather than only how it is Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense Takes initiative to learn how AI/ML technology is evolving outside the organization Takes initiative to learn how the system can be improved for the customers Should make problems open new doors for innovations Communication: Communicates complex AI/ML concepts internally with ease Accountability: Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play Leadership: Disagree without being disagreeable Use conflict as a way to drill deeper and arrive at better decisions Frequent mentorship Builds ad-hoc cross-department teams for specific projects or problems Can achieve broad scope 'buy in' across project teams and across departments Takes calculated risks Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications B.E/B.Tech/MCA/MSc/MTech (Minimum 16 years of formal education, Correspondence courses are not relevant) 5+ years of experience working on multiple layers of technology Experience deploying and maintaining ML models in production Experience in Agile teams Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.) Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI) Ability to design, implement, and maintain CI/CD pipelines for MLOps and DevOps function Familiarity with traditional software monitoring, scaling, and quality management (QMS) Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Demonstrate hands-on knowledge of OpenSource adoption and use cases Good understanding of Data/Information security Proficient in Data Structures, ML Algorithms, and ML lifecycle Product/Project/Program Related Tech Stack: Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch Programming Languages: Python, R, Java Data Processing: Pandas, NumPy, Spark Visualization: Matplotlib, Seaborn, Plotly Familiarity with model versioning tools (MLFlow, etc.) Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI GenAI: OpenAI, Langchain, RAG etc. Demonstrate good knowledge in Engineering Practices Demonstrates excellent problem-solving skills Proven excellent verbal, written, and interpersonal communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. Show more Show less

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. What Primary Responsibilities: Business Knowledge: Capable of understanding the requirements for the entire project (not just own features) Capable of working closely with PMG during the design phase to drill down into detailed nuances of the requirements Has the ability and confidence to question the motivation behind certain requirements and work with PMG to refine them. Design: Can design and implement machine learning models and algorithms Can articulate and evaluate pros/cons of different AI/ML approaches Can generate cost estimates for model training and deployment Coding/Testing: Builds and optimizes machine learning pipelines Knows & brings in external ML frameworks and libraries Consistently avoids common pitfalls in model development and deployment How Quality: Solves cross-functional problems using data-driven approaches Identifies impacts/side effects of models outside of immediate scope of work Identifies cross-module issues related to data integration and model performance Identifies problems predictively using data analysis Productivity: Capable of working on multiple AI/ML projects simultaneously and context switching between them Process: Enforces process standards for model development and deployment. Independence: Acts independently to determine methods and procedures on new or special assignments Prioritizes large tasks and projects effectively Agility: Release Planning: Works with the PO to do high-level release commitment and estimation Works with PO on defining stories of appropriate size for model development Agile Maturity: Able to drive the team to achieve a high level of accomplishment on the committed stories for each iteration Shows Agile leadership qualities and leads by example WITH Team Work: Capable of working with development teams and identifying the right division of technical responsibility based on skill sets. Capable of working with external teams (e.g., Support, PO, etc.) that have significantly different technical skill sets and managing the discussions based on their needs Initiative: Capable of creating innovative AI/ML solutions that may include changes to requirements to create a better solution Capable of thinking outside-the-box to view the system as it should be rather than only how it is Proactively generates a continual stream of ideas and pushes to review and advance ideas if they make sense Takes initiative to learn how AI/ML technology is evolving outside the organization Takes initiative to learn how the system can be improved for the customers Should make problems open new doors for innovations Communication: Communicates complex AI/ML concepts internally with ease Accountability: Well versed in all areas of the AI/ML stack (data preprocessing, model training, evaluation, deployment, etc.) and aware of all components in play Leadership: Disagree without being disagreeable Use conflict as a way to drill deeper and arrive at better decisions Frequent mentorship Builds ad-hoc cross-department teams for specific projects or problems Can achieve broad scope 'buy in' across project teams and across departments Takes calculated risks Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications B.E/B.Tech/MCA/MSc/MTech (Minimum 16 years of formal education, Correspondence courses are not relevant) 4+ years of experience working on multiple layers of technology Experience deploying and maintaining ML models in production Experience in Agile teams Experience with one or more data-oriented workflow orchestration frameworks (Airflow, KubeFlow etc.) Working experience or good knowledge of cloud platforms (e.g., Azure, AWS, OCI) Ability to design, implement, and maintain CI/CD pipelines for MLOps and DevOps function Familiarity with traditional software monitoring, scaling, and quality management (QMS) Knowledge of model versioning and deployment using tools like MLflow, DVC, or similar platforms Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Demonstrate hands-on knowledge of OpenSource adoption and use cases Good understanding of Data/Information security Proficient in Data Structures, ML Algorithms, and ML lifecycle Product/Project/Program Related Tech Stack: Machine Learning Frameworks: Scikit-learn, TensorFlow, PyTorch Programming Languages: Python, R, Java Data Processing: Pandas, NumPy, Spark Visualization: Matplotlib, Seaborn, Plotly Familiarity with model versioning tools (MLFlow, etc.) Cloud Services: Azure ML, AWS SageMaker, Google Cloud AI GenAI: OpenAI, Langchain, RAG etc. Demonstrate good knowledge in Engineering Practices Demonstrates excellent problem-solving skills Proven excellent verbal, written, and interpersonal communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone - of every race, gender, sexuality, age, location and income - deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. Show more Show less

About The Role Mandatory SkillGen AI, LLM, GPT-3, RAG, Lang chain, Llama, AI/ML, DL, NLP or Computer Vision, Python, Tensorflow, Pytorch, Django, Keras, Pandas, NumPy Preferred SkillAWS or GCP or Azure Cloud, MLOps, GPT-4, SQL, Scikit-learn, Matplotlib, Seaborn, Hadoop, Spark, or Apache Flink, Banking exposure Required Skill Programming LanguagesProficiency in Python, R, or Java. Experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, etc. Machine LearningStrong understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning. Data ScienceExperience with data analysis, data visualization, and statistical modeling. Proficiency in using tools like Pandas, NumPy, Matplotlib, and Seaborn. Big Data TechnologiesFamiliarity with big data processing frameworks like Hadoop, Spark, or Apache Flink. Cloud PlatformsExperience with cloud services such as AWS, Google Cloud, or Azure for deploying AI solutions. Natural Language Processing (NLP)Knowledge of NLP techniques and tools such as NLTK, SpaCy, or GPT-3. Computer VisionExperience with computer vision techniques and libraries such as OpenCV, YOLO, or Fast R-CNN. Problem-SolvingStrong analytical and problem-solving skills with the ability to think critically and creatively. CommunicationExcellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Team CollaborationAbility to work effectively in a collaborative team environment and contribute to team success. Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

Job Description As a Principal AI Engineer, he will be part of a high performing team working on exciting opportunities in AI within Ford Credit. We are looking for a highly skilled, technical, hands-on AI engineer with a solid background in building end-to-end AI applications, exhibiting a strong aptitude for learning and keeping up with the latest advances in AIDevelop Machine Learning (Supervised/Unsupervised learning), Neural Networks (ANN, CNN, RNN, LSTM, Decision tree, Encoder, Decoder), Natural Language Processing, Generative AI (LLMs, Lang Chain, RAG, Vector Database) . He should be able to lead technical discussion and technical mentor for the team. Responsibilities Excellent in communication and presentation skills. Ability to do stakeholder management. Ability to collaborate with a cross-functional team involving data engineers, solution architects, application engineers, and product teams across time zones to develop data and model pipelines. Ability to drive and mentor the team technically, leveraging cutting edge AI and Machine Learning principles and develop production-ready AI solutions. Mentor the team of data scientists and assume responsible for the delivery of use cases. Ability to scope the problem statement, data preparation, training and making the AI model production ready. Work with business partners to understand the problem statement, translate the same into analytical problem. Ability to manipulate structured and unstructured data. Develop, test and improve existing machine learning models. Analyse large and complex data sets to derive valuable insights. Research and implement best practices to enhance existing machine learning infrastructure. Develop prototypes for future exploration. Design and evaluate approaches for handling large volume of real data streams. Ability to determine appropriate analytical methods to be used. Understanding of statistics and hypothesis testing. Qualifications Professional Experience: Potential candidates should possess 10+ years of strong working experience in AI. BE/MSc/ MTech /ME/PhD (Computer Science/Maths, Statistics). Possess a strong analytical mindset and be very comfortable with data. Experience with handling both relational and non-relational data. Hands-on experience with analytics methods (descriptive/predictive/prescriptive), Statistical Analysis, Probability and Data Visualization tools (Python-Matplotlib, Seaborn). Background of Software engineering with excellent Data Science working experience. Technical Experience: Develop Machine Learning (Supervised/Unsupervised learning), Neural Networks (ANN, CNN, RNN, LSTM, Decision tree, Encoder, Decoder), Natural Language Processing, Generative AI (LLMs, Lang Chain, RAG, Vector Database) . Show more Show less

Job Title: Python Developer Experience: 1 – 3 Years Location: Perungudi, Chennai (Work From Office) Shift Timings: Regular Shift: 10:00 AM – 7:00 PM Late Shift: 1:00 PM – 10:00 PM (Shifts alternate every two weeks). We are hiring a Python Developer to join the Market Risk team of a global organization in Chennai. This role involves developing and maintaining risk analytics tools and automating reporting processes to support commodity risk management. Key Responsibilities: Develop, test, and maintain Python scripts for data analysis and reporting Write scalable, clean code using Pandas, NumPy, Matplotlib, and OOPS principles Collaborate with risk analysts to implement process improvements Document workflows and maintain SOPs in Confluence Optimize code performance and adapt to evolving business needs Requirements: Strong hands-on experience with Python, Pandas, NumPy, Matplotlib, and OOPS Good understanding of data structures and algorithms Experience with Excel and VBA is an added advantage Exposure to financial/market risk environments is preferred Excellent problem-solving, communication, and documentation skills Interested candidates, please share your updated CV to: janani.sivanandam@antal.com Show more Show less

Design and conduct statistical analysis of large and complex educational datasets to generate actionable insights Build analytical models to uncover trends, test hypotheses, and support data-driven policy decisions Develop and maintain interactive dashboards and visualizations that communicate insights clearly to nontechnical stakeholders Conduct diagnostic and predictive analysis using sound statistical methodologies Collaborate with internal teams and government stakeholders to translate insights into strategic program or policy recommendations Support data cleaning, preparation, and management processes to ensure high data integrity across sources Contribute to the design of data collection frameworks for new education initiatives Prepare high-quality analytical reports and documents that summarize findings Document methodologies, analysis processes, and assumptions used during data analysis to ensure reproducibility and transparency Who we are looking for: We are seeking a recent graduate or early-career professional with strong technical and analytical skills. The ideal candidate will have: Freshers or candidates with upto 2 years of experience. A strong academic background in Statistics, Econometrics, or a related quantitative field (e.g., M.Sc. in Statistics) Deep understanding of statistical techniques, including regression, clustering, hypothesis testing, timeseries analysis, and multi-variate analysis Proficiency in at least one programming language for statistical analysis: R or Python Strong data visualization skills using tools such as Tableau, Looker Studio, Power BI, or libraries like ggplot, matplotlib, seaborn Hands-on experience with SQL-based databases (e.g., MySQL, PostgreSQL) and familiarity with NoSQL databases (e.g., MongoDB, Firebase) Ability to clearly present complex data in compelling and accessible formats to diverse stakeholders Excellent problem-solving, analytical thinking, and communication skills High level of self-motivation, attention to detail, and alignment with EdIndias mission of transforming public education through data Preferred Skills: Experience with cloud platforms such as AWS or Google BigQuery Exposure to software development tools like Python (for scripting or automation) or Flutter (for app or dashboard development) Understanding of education data systems or prior experience working with government/public sector datasets Why Join Us: Opportunity to work on impactful, data driven education projects. Collaborative and growth-oriented work environment. Hands-on experience with real-world datasets and decision-making processes A chance to contribute to the transformation of education in India.

Strong working experience in python based Django,Flask framework. Experience in developing microservices based design and architecture. Strong programming knowledge in Javascript,HTML5, Python, Restful API, gRPC API Programming experience & object-oriented concepts in PYTHON. Knowledge of python libraries like Numpy, Pandas, Ppen3D, OpenCV, Matplotlib. Knowledge of MySQL/Postgres/MSSQL database. Knowledge of 3D geometry. Knowledge of SSO/OpenID Connect/OAuth authentication protocols. Working experience with version control systems like GitHub/BitBucket/GitLab. Familiarity with continuous integration and continuous deployment (CI/CD) pipelines. Basic knowledge of image processing. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. - Grade Specific Has more than a year of relevant work experience. Solid understanding of programming concepts, software design and software development principles. Consistently works to direction with minimal supervision, producing accurate and reliable results. Individuals are expected to be able to work on a range of tasks and problems, demonstrating their ability to apply their skills and knowledge. Organises own time to deliver against tasks set by others with a mid term horizon. Works co-operatively with others to achieve team goals and has a direct and positive impact on project performance and make decisions based on their understanding of the situation, not just the rules.

"Strong working experience in python based Django,Flask framework. Experience in developing microservices based design and architecture. Strong programming knowledge in Javascript,HTML5, Python, Restful API, gRPC API Programming experience & object-oriented concepts in PYTHON. Knowledge of python libraries like Numpy, Pandas, Ppen3D, OpenCV, Matplotlib. Knowledge of MySQL/Postgres/MSSQL database. Knowledge of 3D geometry. Knowledge of SSO/OpenID Connect/OAuth authentication protocols. Working experience with version control systems like GitHub/BitBucket/GitLab. Familiarity with continuous integration and continuous deployment (CI/CD) pipelines. Basic knowledge of image processing. Knowledge of data-analysis, data science. Strong communication skills. Very good in analytical & logical thinking on different perspectives. Ability to handle challenges & resolve any blockers. Good team player & proactive in giving new ideas/suggestions/solutions & constructive analysis of team member's ideas. Interested to working in a fast-paced, Agile software development team Good to Have: Knowledge of other programming language like C, C++. Knowledge of basics of machine-learning. Exposure to NoSQL Databases. Knowledge of GCP/AWS/Azure cloud" Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. - Grade Specific Is fully competent in it's own area and has a deep understanding of related programming concepts software design and software development principles. Works autonomously with minimal supervision. Able to act as a key contributor in a complex environment, lead the activities of a team for software design and software development. Acts proactively to understand internal/external client needs and offers advice even when not asked. Able to assess and adapt to project issues, formulate innovative solutions, work under pressure and drive team to succeed against its technical and commercial goals. Aware of profitability needs and may manage costs for specific project/work area. Explains difficult concepts to a variety of audiences to ensure meaning is understood. Motivates other team members and creates informal networks with key contacts outside own area. Skills (competencies) Verbal Communication

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 2 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve collaborating with cross-functional teams to design and implement production-ready solutions, ensuring that the applications meet high-quality standards. You will also explore the integration of generative AI models into various projects, contributing to innovative solutions that enhance user experiences and operational efficiency. Your role will require a blend of technical expertise and creative problem-solving to address complex challenges in the field of artificial intelligence and machine learning. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Assist in the design and implementation of AI-driven applications and systems.- Collaborate with team members to troubleshoot and resolve technical issues. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Good To Have Skills: Experience with cloud-based AI services.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with natural language processing techniques and tools.- Experience in developing and deploying chatbots and conversational agents. Additional Information:- The candidate should have minimum 2 years of experience in Large Language Models.- This position is based at our Pune office.- A 15 years full time education is required. Qualification 15 years full time education

As an Associate Data Scientist at IBM, you will work to solve business problems using leading edge and open-source tools such as Python, R, and TensorFlow, combined with IBM tools and our AI application suites. You will prepare, analyze, and understand data to deliver insight, predict emerging trends, and provide recommendations to stakeholders. In your role, you may be responsible for: Implementing and validating predictive and prescriptive models and creating and maintaining statistical models with a focus on big data & incorporating machine learning. techniques in your projects Writing programs to cleanse and integrate data in an efficient and reusable manner Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors Communicating with internal and external clients to understand and define business needs and appropriate modelling techniques to provide analytical solutions. Evaluating modelling results and communicating the results to technical and non-technical audiences Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Document solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides Preferred technical and professional experience Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms Experience and working knowledge in COBOL & JAVA would be preferred

An AI Data Scientist at IBM is not just a job title - it’s a mindset. You’ll leverage the watsonx,AWS Sagemaker,Azure Open AI platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. We are seeking an experienced and innovative AI Data Scientist to be specialized in foundation models and large language models. In this role, you will be responsible for architecting and delivering AI solutions using cutting-edge technologies, with a strong focus on foundation models and large language models. You will work closely with customers, product managers, and development teams to understand business requirements and design custom AI solutions that address complex challenges. Experience with tools like Github Copilot, Amazon Code Whisperer etc. is desirable. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Help in showcasing the ability of Gen AI code assistant to refactor/rewrite and document code from one language to another, particularly COBOL to JAVA through rapid prototypes/ PoC Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Experience and working knowledge in COBOL & JAVA would be preferred o Having experience in Code generation, code matching & code translation leveraging LLM capabilities would be a Big plus (e.g. Amazon Code Whisperer, Github Copilot etc.) Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Experience in python and pyspark will be added advantage Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms. Strong track record in scientific publications or open-source communities Experience in full AI project lifecycle, from research and prototyping to deployment in production environments

An AI Engineer at IBM is not just a job title - it's a mindset. You'll leverage the watsonx platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Collaboration and Project ManagementCollaborate with cross-functional teams, including data scientists, software engineers, and project managers, to ensure smooth execution and successful delivery of AI solutions. Effectively communicate project progress, risks, and dependencies to stakeholders. Customer Engagement and SupportAct as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Required Technical and Professional Expertise EducationBachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges

About Us Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry. In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services. Who You Will Work With The Consumer Products Center of Expertise collaborates with Bain’s global Consumer Products Practice leadership, client-facing Bain leadership and teams, and with end clients on development and delivery of Bain’s proprietary CP products and solutions. These solutions aim to answer strategic questions of Bain’s CP clients relating to brand strategy (consumer needs, assortment, pricing, distribution), revenue growth management (pricing strategy, promotions, profit pools, trade terms), negotiation strategy with key retailers, optimization of COGS etc. You will work as part of the team in CP CoE comprising of a mix of Director, Managers, Projects Leads, Associates and Analysts working to implement cloud-based end-to-end advanced analytics solutions. Delivery models on projects vary from working as part of a CP Center of Expertise, broader global Bain case team within the CP ringfence, or within other industry CoEs such as FS / Retail / TMT / Energy / CME / etc with BCN on need basis What You’ll Do Lead AI Initiatives: Architect and implement AI-driven solutions for Consumer Products consulting and client delivery AI & Machine Learning: Develop and deploy Generative AI-based solutions, leveraging cloud computing platforms (AWS/ Azure/GCP) Technical Leadership: Guide the team in AI, machine learning, and data engineering, ensuring optimal architecture and deployment Software Development & Data Engineering: Hands-on experience with Python programming, microservices architecture, and cloud technologies (AWS) Database: Proven experience with database systems such as SQL Server, PostgreSQL, good to have knowledge of Snowflake, Oracle Frontend and Backend Technologies: Exposure to HTML, CSS, Javascript, ReactJS and FastAPI, Django Python Libraries: Exposure to data analysis and visualization libraries like Matplotlib, Plotly, Pandas, Numpy etc. Prompt Engineering & Generative AI: Strong understanding of LLMs, NLP, Chains, Agents and AI model fine-tuning Client Engagement: Work in client-facing roles, understand business needs, and translate them into AI-driven solutions Strategic AI Roadmap: Identify technical limitations, propose alternative approaches, and ensure the scalability of AI applications About You 8+ years of experience in Data Engineering, Software Engineering, and AI/ML Experience in CPG consulting and client delivery Expertise in Python, Generative AI, and cloud computing (AWS/Azure/GCP) Hands-on experience with microservices architecture and chatbot development Adept at Prompt Engineering and AI model optimization Proven track record of leading AI-driven projects with a strategic and solution-oriented mindset Experience in client-facing roles, managing interactions and delivering AI- AI-powered business solutions Prior experience in AI-driven consulting for the Consumer Products industry. Exposure to LLM-based applications Ability to bridge the gap between business and technology, translating client needs into actionable AI solutions What Makes Us a Great Place To Work We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the #1 consulting firm on Glassdoor’s Best Places to Work list, and we have maintained a spot in the top four on Glassdoor's list for the last 12 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents.. Show more Show less

An AI Engineer at IBM is not just a job title - it's a mindset. You'll leverage the watsonx platform to co-create AI value with clients, focusing on technology patterns to enhance repeatability and delight clients. Success is our passion, and your accomplishments will reflect this, driving your career forward, propelling your team to success, and helping our clients to thrive. Day-to-Day Duties: Proof of Concept (POC) DevelopmentDevelop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs, ensuring alignment with customer requirements and expectations. Collaboration and Project ManagementCollaborate with cross-functional teams, including data scientists, software engineers, and project managers, to ensure smooth execution and successful delivery of AI solutions. Effectively communicate project progress, risks, and dependencies to stakeholders. Customer Engagement and SupportAct as a technical point of contact for customers, addressing their questions, concerns, and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases. Documentation and Knowledge SharingDocument solution architectures, design decisions, implementation details, and lessons learned. Create technical documentation, white papers, and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members. Industry Trends and InnovationStay up to date with the latest trends and advancements in AI, foundation models, and large language models. Evaluate emerging technologies, tools, and frameworks to assess their potential impact on solution design and implementation. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise EducationBachelor's, Master's, or Ph.D. degree in Computer Science, Artificial Intelligence, Data Science or a related field. Technical Skills: Strong programming skills, with proficiency in Python and experience with AI frameworks such as TensorFlow, PyTorch, Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn, Pandas, Matplotlib, etc. Familiarity with cloud platforms (e.g. Kubernetes, AWS, Azure, GCP) and related services is a plus. Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI. Growth mindsetDemonstrate a growth mindset to understand clients' business processes and challenges. Preferred technical and professional experience ExperienceProven experience in designing and delivering AI solutions, with a focus on foundation models, large language models, exposure to open source, or similar technologies. Experience in natural language processing (NLP) and text analytics is highly desirable. Understanding of machine learning and deep learning algorithms.

About us Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry. In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services. Who you will work with The Consumer Products Center of Expertise collaborates with Bain’s global Consumer Products Practice leadership, client-facing Bain leadership and teams, and with end clients on development and delivery of Bain’s proprietary CP products and solutions. These solutions aim to answer strategic questions of Bain’s CP clients relating to brand strategy (consumer needs, assortment, pricing, distribution), revenue growth management (pricing strategy, promotions, profit pools, trade terms), negotiation strategy with key retailers, optimization of COGS etc. You will work as part of the team in CP CoE comprising of a mix of Director, Managers, Projects Leads, Associates and Analysts working to implement cloud-based end-to-end advanced analytics solutions. Delivery models on projects vary from working as part of a CP Center of Expertise, broader global Bain case team within the CP ringfence, or within other industry CoEs such as FS / Retail / TMT / Energy / CME / etc with BCN on need basis What you’ll do Lead AI Initiatives : Architect and implement AI-driven solutions for Consumer Products consulting and client delivery AI & Machine Learning : Develop and deploy Generative AI-based solutions , leveraging cloud computing platforms (AWS/ Azure/GCP) Technical Leadership : Guide the team in AI, machine learning, and data engineering , ensuring optimal architecture and deployment Software Development & Data Engineering : Hands-on experience with Python programming, microservices architecture, and cloud technologies (AWS) Database: Proven experience with database systems such as SQL Server, PostgreSQL, good to have knowledge of Snowflake, Oracle Frontend and Backend Technologies : Exposure to HTML, CSS, Javascript, ReactJS and FastAPI, Django Python Libraries: Exposure to data analysis and visualization libraries like Matplotlib, Plotly, Pandas, Numpy etc. Prompt Engineering & Generative AI : Strong understanding of LLMs, NLP, Chains, Agents and AI model fine-tuning Client Engagement : Work in client-facing roles, understand business needs, and translate them into AI-driven solutions Strategic AI Roadmap : Identify technical limitations , propose alternative approaches, and ensure the scalability of AI applications About you 8+ years of experience in Data Engineering, Software Engineering, and AI/ML Experience in CPG consulting and client delivery Expertise in Python, Generative AI, and cloud computing (AWS/Azure/GCP) Hands-on experience with microservices architecture and chatbot development Adept at Prompt Engineering and AI model optimization Proven track record of leading AI-driven projects with a strategic and solution-oriented mindset Experience in client-facing roles , managing interactions and delivering AI- AI-powered business solutions Prior experience in AI-driven consulting for the Consumer Products industry . Exposure to LLM-based applications Ability to bridge the gap between business and technology , translating client needs into actionable AI solutions What makes us a great place to work We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity and a model of social responsibility. We are currently ranked the #1 consulting firm on Glassdoor’s Best Places to Work list, and we have maintained a spot in the top four on Glassdoor's list for the last 12 years. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. We are publicly recognized by external parties such as Fortune, Vault, Mogul, Working Mother, Glassdoor and the Human Rights Campaign for being a great place to work for diversity and inclusion, women, LGBTQ and parents..

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY GDS – AI and DATA – Statistical Modeler-Senior At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. As part of our EY- GDS AI and Data team, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Banking, Insurance, Manufacturing, Healthcare, Retail, Manufacturing and Auto, Supply Chain, and Finance. Technical Skills: Statistical Programming Languages: Python, R Libraries & Frameworks: Pandas, NumPy, Scikit-learn, StatsModels, Tidyverse, caret Data Manipulation Tools: SQL, Excel Data Visualization Tools: Matplotlib, Seaborn, ggplot2, Machine Learning Techniques: Supervised and unsupervised learning, model evaluation (cross-validation, ROC curves) 5-7 years of experience in building statistical forecast models for pharma industry Deep understanding of patient flows,treatment journey across both Onc and Non Onc Tas. What we look for A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction and advisory services, we’re using the finance products, expertise and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description (Shaded areas for Talent use only) We are seeking a passionate data analyst to transform data into actionable insights and support decision-making in a global organization focused on pricing and commercial strategy. This role spans business analysis, requirements gathering, data modeling, solution design, and visualization using modern tools. The analyst will also maintain and improve existing analytics solutions, interpret complex datasets, and communicate findings clearly to both technical and non-technical audiences. Essential Functions of the Job: (Identify and describe essential functions, or primary duties and responsibilities. Each function should describe WHAT is done and the END RESULT/PURPOSE achieved. Assume that the reader does not know the role or function of the job.) Analyze and interpret structured and unstructured data using statistical and quantitative methods to generate actionable insights and ongoing reports. Design and implement data pipelines and processes for data cleaning, transformation, modeling, and visualization using tools such as Power BI, SQL, and Python. Collaborate with stakeholders to define requirments, prioritize business needs, and translate problems into analytical solutions. Develop, maintain, and enhance scalable analytics solutions and dashboards that support pricing strategy and commercial decision-making. Identify opportunities for process improvement and opperational efficiency through data-driven recommendations. Communicate complex findings in a clear, compelling, and actionable manner to both technical and non-technical audiences. Analytical/Decision Making Responsibilities: (Describe the kind of problems and challenges typically faced, and decisions required to perform the job, as well as recommendations made to supervisors or others. Focus on the nature of existing policies, precedents and procedures used to guide decisions, and the degree to which the incumbent is free to make decisions requiring interpretation and judgment. Provide an example.) Apply a hypothesis-driven approach to analyzing ambiguous or complex data and synthesizing insights to guide strategic decisions. Promote adoption of best practices in data analysis, modeling, and visualization, while tailoring approaches to meet the unique needs of each project. Tackle analytical challenges with creativity and rigor, balancing innovative thinking with practical problem-solving across varied business domains. Prioritize work based on business impact and deliver timely, high-quality results in fast-paced environments with evolving business needs. Demonstrate sound judgement in selecting methods, tools, and data sources to support business objectives. Knowledge and Skills Requirements: (Describe the knowledge or skills needed to perform this job; these may be professional, technical, or managerial) Proven experience as a data analyst, business analyst, data engineer, or similar role. Strong analytical skills with the ability to collect, organize, analyze, and present large datasets accurately. Foundational knowledge of statistics, including concepts like distributions, variance, and correlation. Skilled in documenting processes and presenting findings to both technical and non-technical audiences. Hands-on experience with Power BI for designing, developing, and maintaining analytics solutions. Proficient in both Python and SQL, with strong programming and scripting skills. Skilled in using Pandas, T-SQL, and Power Query M for querying, transforming, and cleaning data. Hands-on experience in data modeling for both transactional (OLTP) and analytical (OLAP) database systems. Strong visualization skills using Power BI and Python libraries such as Matplotlib and Seaborn. Experience with defining and designing KPIs and aligning data insights with business goals. Additional/Optional Knowledge and Skills: (Describe any additional knowledge or skills that, while not required, may be useful or helpful to perform this job; these may be professional, technical, or managerial) Experience with the Microsoft Fabric data analytics environment. Proficiency in using the Apache Spark distributed analytics engine, particularly via PySpark and Spark SQL. Exposure to implementing machine learning or AI solutions in a business context. Familiarity with Python machine learning libraries such as scikit-learn, XGBoost, PyTorch, or transformers. Experience with Power Platform tools (Power Apps, Power Automate, Dataverse, Copilot Studio, AI Builder). Knowledge of pricing, commercial strategy, or competitive intelligence. Experience with cloud-based data services, particularly in the Azure ecosystem (e.g., Azure Synapse Analytics or Azure Machine Learning). Supervision Responsibilities: (Describe the level of supervision received, i.e., the frequency of supervisory contact, degree to which the individual acts independently and on what kinds of issues. Describe the level of supervision of others, if any, i.e., assigning work, reviewing performance, direct or indirect responsibility). Operates with a high degree of independence and autonomy. Collaborates closesly with cross-functional teams including sales, pricing, and commercial strategy. Mentors junior team members, helping develop technical skills and business domain knowledge. Other Requirements: (Describe any miscellaneous functions or expectations of the job that are important to note) Collaborates with a team operating primarily in the Eastern Time Zone (UTC 4:00 / 5:00). Limited travel may be required for this role. Job Requirements: Education: (What is the minimum level of education or equivalent experience needed/suggested to perform this job effectively?) A bachelor’s degree in a STEM field relevant to data analysis, data engineering, or data science is required. Examples include (but are not limited to) computer science, statistics, data analytics, artificial intelligence, operations research, or econometrics. Experience: (What is the minimum number or range of years needed to perform this job?) 3–6 years of experience in data analysis, data engineering, or a closely related field, ideally within a professional services enviornment. Certification Requirements: (Describe and explain any certifications and/or licenses needed or helpful to perform this job). No certifications are required for this role. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.

Position Title: AI/ML Engineer Company : Cyfuture India Pvt. Ltd. Industry : IT Services and IT Consulting Location : Sector 81, NSEZ, Noida (5 Days Work From Office) Website : www.cyfuture.com About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e.g., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise 1. Cloud Computing & Deployment Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. 2. Machine Learning & Deep Learning Strong command of frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. 3. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI, Flask, or Django. Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). 4. Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing: Apache Spark, Dask, Ray. 5. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning. A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. 6. Resource Optimization Efficient use of compute resources: GPUs, TPUs, CPUs. Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. 7. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports. Show more Show less

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities, collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. Your role As a Senior Data Scientist, you are expected to develop and implement Artificial Intelligence based solutions across various disciplines for the Intelligent Industry vertical of Capgemini Invent. You are expected to work as an individual contributor or along with a team to help design and develop ML/NLP models as per the requirement. You will work closely with the Product Owner, Systems Architect and other key stakeholders right from conceptualization till the implementation of the project. You should take ownership while understanding the client requirement, the data to be used, security & privacy needs and the infrastructure to be used for the development and implementation. The candidate will be responsible for executing data science projects independently to deliver business outcomes and is expected to demonstrate domain expertise, develop, and execute program plans and proactively solicit feedback from stakeholders to identify improvement actions. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with stakeholders from different functional and business teams. The role also requires the candidate to collaborate on ML asset creation and eager to learn and impart trainings to fellow data science professionals. We expect thought leadership from the candidate, especially on proposing to build a ML/NLP asset based on expected industry requirements. Experience in building Industry specific (e.g. Manufacturing, R&D, Supply Chain, Life Sciences etc), production ready AI Models using microservices and web-services is a plus. Programming Languages – Python – NumPy, SciPy, Pandas, MatPlotLib, Seaborne Databases – RDBMS (MySQL, Oracle etc.), NoSQL Stores (HBase, Cassandra etc.) ML/DL Frameworks – SciKitLearn, TensorFlow (Keras), PyTorch, Big data ML Frameworks - Spark (Spark-ML, Graph-X), H2O Cloud – Azure/AWS/GCP Your Profile Predictive and Prescriptive modelling using Statistical and Machine Learning algorithms including but not limited to Time Series, Regression, Trees, Ensembles, Neural-Nets (Deep & Shallow – CNN, LSTM, Transformers etc.). Experience with open-source OCR engines like Tesseract, Speech recognition, Computer Vision, face recognition, emotion detection etc. is a plus. Unsupervised learning – Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, good understanding of common matrix decomposition approaches like SVD. Various Clustering approaches – Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based clustering like Spectral. NLP – Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping/Understanding, Intent Classification, Word Embeddings, Vector Space Models, experience with libraries like NLTK, Spacy, Stanford Core-NLP is a plus. Usage of Transformers for NLP and experience with LLMs like (ChatGPT, Llama) and usage of RAGs (vector stores like LangChain & LangGraps), building Agentic AI applications. Model Deployment – ML pipeline formation, data security and scrutiny check and ML-Ops for productionizing a built model on-premises and on cloud. Required Qualifications: Master’s degree in a quantitative field such as Mathematics, Statistics, Machine Learning, Computer Science or Engineering or a bachelor’s degree with relevant experience. Good experience in programming with languages such as Python/Java/Scala, SQL and experience with data visualization tools like Tableau or Power BI. Preferred Experience: Experienced in Agile way of working, manage team effort and track through JIRA Experience in Proposal, RFP, RFQ and pitch creations and delivery to the big forum. Experience in POC, MVP, PoV and assets creations with innovative use cases Experience working in a consulting environment is highly desirable. Presupposition: High Impact client communication The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face. What You Will Love About Working Here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. Show more Show less

Who Are We Looking For We are looking for a passionate Full Stack Intern who is eager to work on both frontend and backend technologies. This internship offers a real-world opportunity to develop scalable, secure, and user-friendly web applications. What You Will Be Doing Interns may be involved in learning and contributing to the following areas: Full-Stack Web Development Frontend Development: HTML5, CSS3, JavaScript Angular Framework (Components, Services, Routing, etc.) Responsive Design, Bootstrap, and UI Libraries Backend Development: .NET Core (Web APIs, MVC) RESTful Services and Integration Database: SQL Server or equivalent Schema Design, Stored Procedures, and CRUD Operations Manual Quality Assurance (QA) Introduction to QA methodologies and the software testing lifecycle (STLC) Writing and executing test cases Bug reporting and tracking (using tools like Excel, Trello, Jira, or others) Functional, Regression, UI/UX Testing Cross-browser and cross-device testing Understanding SDLC and QA’s role in Agile environments User Experience (UX) Design (if aligned with intern interest) Fundamentals of UX Design Wireframing and Prototyping Tools (e.g., Figma) Usability Testing and User Feedback Integration Embedded Systems & IoT (Optional Track) Introduction to Arduino and Microcontroller Programming Sensor Integration, Circuit Design, and Testing Basics of Embedded C/C++ and IoT Protocols Real-world Mini Projects using Arduino or similar platforms Basic Artificial Intelligence with Python Python Programming Basics and Libraries (NumPy, Pandas, Matplotlib) Introduction to AI & Machine Learning Concepts Data Preprocessing and Visualization Building Basic Models with Scikit-learn Mini Projects such as: Spam Detection Sentiment Analysis Basic Image Classification Optional: Exploring Chatbots or AI-integrated web features Bonus Points for Familiarity with By the end of the internship, based on the interest and self learning efforts, the interns will be able to: Build and deploy a basic full-stack web application. Understand the software development lifecycle and version control systems (e.g., Git). Optionally demonstrate prototypes or hardware solutions in the embedded domain. Educational Requirement Good understanding of both frontend and backend web development. Experience with React.js (or similar frontend frameworks). Knowledge of Node.js, Express.js, and working with databases. Problem-solving mindset and willingness to learn. Good Communication Skills, Self learner willing to do tasks Salary This is an unpaid internship for 6 months. There will be no salary during the internship period . However, a full-time employment opportunity may be offered to high-performing interns based on their commitment, growth, and contributions after succesful completion of internship and can be discussed once shortlisted. Working Days Mondat - Friday Working Hours 8-9 Hours Onsite Perks & Benefits You'll Get Mentorship from experienced developers. Hands-on experience in real-time projects. Internship Certificate after successful completion. Job offer based on learning, contribution & performance. Show more Show less

Join us as a "Chief Control Office" , where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences. You may be assessed on the key critical skills relevant for success in role, such as experience with MS office, SQL, Alteryx, Power Tools, Python as well as job-specific skillsets. To be successful as an "Analyst", you should have experience with: Basic/ Essential Qualifications: Graduate in any discipline Experience in Controls, Governance, Reporting and Risk Management preferably in a financial services organisation Proficient in MS Office – PPT, Excel, Work & Visio Proficient in SQL, Alteryx and Python Generating Data Insights and Dashboards from large and diverse data sets Excellent experience on Tableau, Alteryx, MS Office (i.e. Advance Excel, PowerPoint) Automation skills using VBA, PowerQuery, PowerApps, etc. Experience in using ETL tools. Good understanding of Risk and Control Excellent communication skills (Verbal and Written) Good understanding of governance and control frameworks and processes Highly motivated, business-focussed and forward thinking. Experience in senior stakeholder management. Ability to manage relationships across multiple disciplines Desirable skillsets/ good to have: Experience in data crunching/ analysis including automation Experience in handling RDBMS (i.e. SQL/Oracle) Experience in Python, Data Science and Data Analytics Tools and Techniques e.g. MatPlotLib, Data Wrangling, Low Code/No Code environment development preferably in large bank on actual use cases Understanding of Data Management Principles and data governance Design and managing SharePoints Financial Services experience Show more Show less