2726 Data Science Jobs - Page 23

Main Responsibilities are: Understand, Define and Articulate the art of possible of AI/ML/MLOps solutions to Business heads. Hands-on in Designing, Development and Production roll-out of AI / ML/ MLOps solutions using data science framework and methodologies (CRISP-DM and TDSP) for complex problems. Must have thorough understanding and hands-on experience of using Statistical Modeling, Classical ML, Bigdata Analytics, Deep Neural Networks, Edge AI, MLOps, Generative AI •. Should have good understanding of functional domain with data, data pipelines, data storage, data lineage and quality data management. Data Analysis and Insights Generation - Perform exploratory data analysis (EDA) on large datasets from manufacturing processes, supply chain, and other verticals to uncover trends, anomalies, and actionable insights. Identify key performance indicators (KPIs) and metrics to monitor operational efficiency, sustainability goals, and process improvements. Write efficient, reusable, and well-documented code in Python for data processing, analysis, and automation of workflows. Leverage the AWS ecosystem (e.g., S3, Redshift, Lambda, Glue) for data storage, processing, and integration. Utilize statistical and machine learning techniques to solve business problems. Collaborate with data scientists, engineers, and plant managers to translate business needs into technical solutions. Coordinate with vendors to integrate third-party tools or datasets as required. Work on strategic innovative data science projects (Generative AI/ Video Analytics/ Prescriptive Analytics/ Diagnostic Analytics/ Bigdata Analytics/ Time series Analytics etc.) with transformative vision. Work with Business Head and CFT to understand their requirements, help them understand the Art of possible, and develop innovative AI solutions. Also provide mentorship and guidance to junior Data analysts and Data Science Interns in architecting solutions and developing them.

Overview The Executive Vice President of the Data Intelligence Group will lead, mentor, and develop a team of Associates and Analysts. This role involves overseeing and driving initiatives related to data migration, data management, architecture, and advanced analytics for our clients. We seek a strategic leader with a proven track record in managing large-scale data projects, advanced analytics, and expertise in Big Data technologies. The ideal candidate will have deep knowledge in Machine Learning (ML), Artificial Intelligence (AI), and a foundational understanding of Generative AI. This position offers a dynamic path for learning and growth, with high exposure to stakeholder management and client engagement. Key Responsibilities: Lead and manage large-scale data migration projects, ensuring successful execution and stakeholder satisfaction Develop and implement data management strategies and architectural frameworks that support business objectives Oversee advanced analytics initiatives, leveraging data to inform strategic decision-making Consult and interact regularly with clients, acting as a thought partner to understand their needs and drive value Collaborate with cross-functional teams to deploy ML models and AI solutions that drive innovation and efficiency Manage teams working across multiple projects for different clients, ensuring high performance and effective collaboration Foster a culture of continuous improvement, encouraging the team to adopt best practices in data engineering and analytics Mentor and develop team members, nurturing talent in areas such as NLP, predictive analytics, and LLMs Stay abreast of industry trends and technologies, ensuring the organization remains competitive in data analytics and management Familiarity with a variety of data-related fields, including but not limited to: Data Engineering and Management Artificial Intelligence (ML, Deep Learning, Generative AI) Cloud Architecture and Analytics (Azure, AWS, GCP) DevOps and Platform Engineering Software Development and Application Architecture Business Intelligence Solutions (Power BI, Tableau) Qualifications 10+ years of experience in data management, solution architecture, analytics, and project oversight Proven experience in managing large-scale data migration and complex analytics projects Strong experience in cloud architecture and solution design Strong background in Machine Learning, AI, and Generative AI Experience in the BFSI sector is preferred Education Bachelors degree in Technology (B.Tech) or Master of Computer Applications (MCA) is required; MBA or MS preferred Compensation The compensation structure will be as per industry standard

Roles and Responsibility Develop and deploy scalable data pipelines using AI/ML techniques. Collaborate with cross-functional teams to identify business problems and develop solutions. Design and implement predictive models to drive business growth. Work with large datasets to extract insights and trends. Develop and maintain technical documentation of data models and algorithms. Stay updated with industry trends and advancements in AI/ML. Job Requirements Strong proficiency in programming languages such as Python or R. Experience with AI/ML frameworks such as TensorFlow or PyTorch. Strong understanding of statistical concepts and machine learning algorithms. Excellent problem-solving skills and attention to detail. Ability to work collaboratively in a team environment. Strong communication and interpersonal skills. Minimum 3 years of experience in a related field.

5 to 7 years of experience in Data Science or Machine Learning roles Proven ability to work on end-to-end ML projectsfrom research to production Conduct in-depth machine learning research and stay updated with state-of-the-art advancements Read, interpret, and implement research papers, especially in the Generative AI domain

We are looking for a Lead Machine Learning Engineer to join the Data Science team with the athena.intelligence division. You will be responsible for the end-to-end development and deployment of machine learning models across a variety of healthcare products and domains, develop roadmaps for development and implementation of data science initiatives, and work collaboratively to influence product and engineering stakeholders. About you: You love to own important work and find it difficult to turn down a good challenge. You have a strong track record of development and evaluation of ML models, and leading projects or teams in development of ML models. You excel at building relationships and influencing at senior leadership levels and possess an eagerness to learn and disseminate new knowledge. You have strong communication skills and enjoy working with colleagues from a variety of technical and non-technical backgrounds. Finally, you have a strong interest in improving healthcare. About the team The data science team is bringing machine learning to bear against the hardest problems in healthcare. We are working with product and engineering leaders across the company to build machine learning into our Best In KLAS suite of products. We work hand-in-hand with platform engineers to deploy state-of-the-art machine learning models using cloud technologies. Job Responsibilities As a leader of the Data Science team, you are expected to stay abreast and evaluate the latest in data science technologies and determine how to incorporate these into our data science best practices . Integrate with and broadly support the data science team in executing developed roadmaps; identify and document project dependencies; coordinate efforts across the team to ensure completion and effectiveness Contribute to the training and development of junior staff members Develop and follow conventions and best practices for modeling, coding, architecture, and statistics; hold other team members accountable for doing so Contribute to the development of internal tools and data science team standards Work collaboratively across the Infrastructure, Platform, UX, and Product organizations to ensure alignment towards business goals Typical Qualifications: Advanced degree (PHD, MS) in relevant field. For example, but not limited to: math, computer science, computer science, data science 8+ years of professional experience designing, building, training, deploying and evaluating machine learning models in production software environments at scale Experience with development and implementation of Deep Learning Models with complex neural network architectures is a bonus Experience with training & fine tuning LLMs & GenAI models is a bonus. Experience collaborating with cross functional teams or leading cross functional efforts Proficiency with python strongly preferred Have strong NLP skills or computer vision experience, AWS experience strongly preferred

Data Scientist Mumbai One of the leading Bank mail at manjeet.kaur@mounttalent.com Whatsapp at 8384077438 Roles and Responsibilities Qualifications • 2-4 years experience in Analytics and Machine Learning & Deep learning(Sentiment Analysis, Text Mining, Entity Extraction, Document Classification, Topic Modeling, Natural Language Understanding (NLU) and Natural Language Generation (NLG)). • Good Experience in Web Scraping or data extraction through Selenium/Scrapy or other frameworks and related libraries (like beautifulsoup). • Knowldge of advanced scraping techniques (like overcoming captcha, proxy, browser fingerprinting, bot detection bypassing,etc) • Working knowledge in various DBs(MySQL, HBase, MongoDB), message queues & Web RestFul APIs. • Expertise in open-source NLP toolkits such as CoreNLP, OpenNLP, NLTK, gensim, LingPipe, Keras, Tensorflow, Mallet, ML/math toolkits such as scikit-learn, MLlib, Theano, NumPyetc. • Experience of Testing & deployment of Machine learning/deep learning projects in the desired platform. • Strong Logical & Analytical skills with good soft & communication skills Industry Preferably from a Technology, ITES, Shared Services or Banking organization Key Responsibilities • Build, Improve and extend NLP capabilities • Select the proper annotated datasets for supervised learning techniques • Use effective text representation techniques to develop useful features • Identify and utilize the correct algorithms for specific NLP projects • Develop NLP projects in accordance with prescribed requirements • Train developed NLP models and evaluated their effectiveness • Conduct statistical analyses of models, and adjust models where possible • Extend machine learning frameworks and libraries for NLP projects Certifications Certification in Google Tensor Flow, Hadoop, Python, PySpark, SQL, R is desirable Employment Type All positions are on fixed term contract on a full-time basis exclusively for ReBIT, initially for a period of five years, extendable by mutual consent Location Navi Mumba

Title : Lead Data Scientist/ML Engineer (6+ years & above) Required Technical Skillset : (GenAI is must) Language : Python , PySpark Framework : Scikit-learn, TensorFlow, Keras, PyTorch, Libraries : NumPy, Pandas, Matplotlib, SciPy, Scikit-learn - DataFrame, Numpy, boto3 Database : Relational Database(Postgres), NoSQL Database (MongoDB) Cloud : AWS cloud platforms Other Tools : Jenkins, Bitbucket, JIRA, Confluence A machine learning engineer is responsible for designing, implementing, and maintaining machine learning systems and algorithms that allow computers to learn from and make predictions or decisions based on data. The role typically involves working with data scientists and software engineers to build and deploy machine learning models in a variety of applications such as natural language processing, computer vision, and recommendation systems. The key responsibilities of a machine learning engineer includes : - Collecting and preprocessing large volumes of data, cleaning it up, and transforming it into a format that can be used by machine learning models. - Model building which includes Designing and building machine learning models and algorithms using techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning. - Evaluating the model performance of machine learning models using metrics such as accuracy, precision, recall, and F1 score. - Deploying machine learning models in production environments and integrating them into existing systems using CI/CD Pipelines, AWS Sagemaker - Monitoring the performance of machine learning models and making adjustments as needed to improve their accuracy and efficiency. - Working closely with software engineers, product managers and other stakeholders to ensure that machine learning models meet business requirements and deliver value to the organization. Requirements and Skills : Mathematics and Statistics : - A strong foundation in mathematics and statistics is essential. - They need to be familiar with linear algebra, calculus, probability, and statistics to understand the underlying principles of machine learning algorithms. Programming Skills : - Should be proficient in programming languages such as Python. - The candidate should be able to write efficient, scalable, and maintainable code to develop machine learning models and algorithms. Machine Learning Techniques : - Should have a deep understanding of various machine learning techniques, such as supervised learning, unsupervised learning, and reinforcement learning and should also be familiar with different types of models such as decision trees, random forests, neural networks, and deep learning. Data Analysis and Visualization : - Should be able to analyze and manipulate large data sets. - The candidate should be familiar with data cleaning, transformation, and visualization techniques to identify patterns and insights in the data. Deep Learning Frameworks : - Should be familiar with deep learning frameworks such as TensorFlow, PyTorch, and Keras and should be able to build and train deep neural networks for various applications. Big Data Technologies : - A machine learning engineer should have experience working with big data technologies such as Hadoop, Spark, and NoSQL databases. - They should be familiar with distributed computing and parallel processing to handle large data sets. Software Engineering : - A machine learning engineer should have a good understanding of software engineering principles such as version control, testing, and debugging. - They should be able to work with software development tools such as Git, Jenkins, and Docker. Communication and Collaboration : - A machine learning engineer should have good communication and collaboration skills to work effectively with cross-functional teams such as data scientists, software developers, and business stakeholders.

About The Role New or Never Normal Job Title: Internal Audit Team Member Corporate Grade: CA fresher"™s Kotak Overview Kotak Mahindra Bank Limited is an Indian banking and financial services company headquartered in Mumbai, India. It offers banking products and financial services for corporate and retail customers in the areas of personal finance, investment banking, life insurance, and wealth management. At Kotak, we expect more from ourselves, than what anyone else expects of us. This way, we are creating a rewarding and delightful experience every day for our customers. We are an equal opportunity employer and we are opposed to discrimination on any grounds. Overall purpose of role As Kotak Internal Audit Member, you will be a part of Kotak Internal Audit Department (IAD) which aims to provide independent, reliable, valued, insightful and timely assurance to the Board and executive management thus demonstrating a role of an ENABLER . This is achieved by looking at the effectiveness of governance, risk/control framework over current and evolving risks, within the current and expected business environment and in accordance with the international standards definition of internal auditing. Kotak IAD is a 200+ member department spread across 5 locations (Mumbai, Ahmedabad, Bangalore, Chennai and Delhi) which is set up to perform Internal Audits for KMBL (Kotak Mahindra Bank Limited) Flagship Company of the Kotak group. A one-stop shop. 4 Strategic Business Units - Consumer Banking, Corporate Banking (Wholesale Banking), Commercial Banking, Treasury. Key Accountabilities Executing the delivery of the Kotak IAD"™s Audit plan for the calendar year. "¢ To assist the Team Supervisor / Team Lead on assigned audit work of KMBL Businesses & Processes. This will entail working on the audit to deliver the Audit Planning Memo, Controls Document, agree issues & action plans with management and submission of draft report to the Team Supervisor. "¢ Demonstrate sound knowledge of both business/technical areas and expert knowledge in the audit process, including the IA systems, to ensure that audit work is carried out with a high standard that meets all methodologies. "¢ Demonstrate sound knowledge of regulations governing the bank (RBI, IRDA, SEBI, FEMA, FIMMDA, FEDAI, FATCA, NDS-OM, etc.) "¢ Conducts reviews to understand end-to-end process, evaluate and highlight key control deficiencies, analyse root cause and discuss / agree with management for effective and timely remediation plans. "¢ Manage individual workflow to ensure timely report deliveries with quality articulation of audit queries "¢ Writing high quality audit reports. To embrace and demonstrate effective Audit report writing & presentation skills from E2E perspective (Planning, Execution, Discussion, Clarification, Finalisation, Documentation into system etc.) "¢ Endeavouring to update awareness of risk issues and changes across relevant business units and use this knowledge to update the audit approach. "¢ Driving and leading discussions with relevant stakeholders regarding audit observations, consulting with IAD team supervisors / Team Leads. Decision-making and Problem Solving Take into account reputation of Kotak at all times, through positive interactions and adhering to policies, procedures and manuals. Set an example and supports fair and ethical behaviour. Make sure you are equipped to be able to protect our reputation at all times. Challenge others where appropriate, if you believe self to be correct. Endeavour to be part in decision making on a broad range of factors, with Kotak"™s values at heart - Always Responsible, Always Accountable. Risk and Control Objective [This section is mandatory for all role profiles] Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Kotak"™s Policies and Standards. Person Specification Personal attributes essential to performing role including competencies, expertise, knowledge, and experience. Noteexperience requirements must not be in the form of years (minimum or otherwise). Essential Skills/Basic & Preferred Qualifications: Understanding of Banking Business their products and processes. "¢ Person who can work alone, close audits and manage stakeholders "¢ Relevant professional qualifications e.g. CA/CMA, CISA, CIA, (Bachelor"™s degree mandatory). "¢ A Bachelor"™s degree in Commerce (preferably) holder with at least3-5 years of experiencein internal audit of a financial institution and/or relevant experience in the following areas: "¢ Experience in a BFSI or Finance processes, including audit. Understanding of relevant regulatory environment would be an added advantage. "¢ Experience in data analytics and/or exposure to data science/machine learning techniques would be an added advantage.

Job Description Key Responsibilities: 1. Data Engineering & Pipeline Development Design, build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. Implement data modeling and feature engineering for ML use cases. 2. Machine Learning Model Development & Validation Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. Optimize models for scalability, efficiency, and interpretability. 3. MLOps & Model Deployment Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. 4. Cloud & Infrastructure Optimization Design cloud-native data processing solutions on Google Cloud Platform (GCP), leveraging services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow. Work on containerized deployment (Docker, Kubernetes) for scalable model inference. Implement cost-efficient, serverless data solutions where applicable. 5. Business Impact & Cross-functional Collaboration Work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translate complex model insights into actionable business recommendations. Present findings and performance metrics to both technical and non-technical stakeholders. Qualifications & Skills: Educational Qualifications: - Bachelors or Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. - Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: - Experience: 5-10 years with the mentioned skillset & relevant hands-on experience - Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). - ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. - Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. - Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. - MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). - Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: - Experience with Graph ML, reinforcement learning, or causal inference modeling. - Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. - Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. - Experience with distributed computing frameworks (Spark, Dask, Ray).

Job Title: Data Scientist Location: Bangalore, India Experience: 3+ Years Role & Responsibilities: We are looking for a highly motivated Data Scientist to join our analytics team in Bangalore. This role is ideal for individuals who possess strong machine learning and data engineering skills and are eager to solve complex problems in the financial technology space. You will work on developing predictive models, building scalable data solutions, and contributing to key decision-making processes. Design, build, and validate machine learning models including Logistic Regression, Random Forests, GBM, and Survival Models. Perform rigorous model evaluation using techniques such as K-Fold Cross Validation, Out-of-Time (OOT) validation, and X-Tab analysis. Utilize Python (via PyCharm/Jupiter), scikit-learn, PyTorch or TensorFlow for end-to-end model development. Analyse large datasets using SQL and Excel to derive actionable insights. Develop and deploy APIs to serve machine learning models in production environments. Apply statistical techniques such as mean/variance analysis, probability distributions, and simulations to drive model accuracy and relevance. (Optional) Work with lending-specific metrics such as vintage curves, roll forward tracking, and bounce rates to enhance financial models. Strong ML skills: Logistic, Random Forest, GBM, survival model, K fold test, OOT, X-Tab etc. Experience using scikit-learn, pytorch or tensor flow. Experience: 3+ Years Python and usage of PyCharm/ Jupiter, SQL, Excel. Well versed in API development - Strong mathematical ability. mean, variance, probability distributions, simulation etc. Understanding of lending metrics such as vintage curve, roll forward, bounces etc. (Good to have not mandatory) Engineering background preferred IIT/NIT plus not must. Prior experience in Lending Fintech preferred.

Role & responsibilities Responsibilities : The responsibilities include teaching a requisite number of classes, providing guidance and supervision to graduate students, participating in departmental meetings, and providing academic support to Professors and other faculty members. You should be able to pace your lessons. Subject - Computer Science, Java, C++ Assisting with various departmental duties and providing academic support to Professors and other staff. Teaching and supervising undergraduate and graduate students. Providing demonstrations and supervising experiments and investigations. Answering questions in class or via email or telephone. Providing Professors and Department Heads with feedback on student progress. Attending faculty and departmental meetings and voicing concerns or providing suggestions for improvement.

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai/Pune Experience: 38 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Databricks, PySpark , and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What Youll Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail : CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com.

Role & responsibilities We are seeking an experienced and technically strong Machine Learning Engineer to design, implement, and operationalize ML models across Google Cloud Platform (GCP) and Microsoft Azure. The ideal candidate will have a robust foundation in machine learning algorithms, MLOps practices, and experience deploying models into scalable cloud environments. Responsibilities: Design, develop, and deploy machine learning solutions for use cases in prediction, classification, recommendation, NLP, and time series forecasting. Translate data science prototypes into production-grade, scalable models and pipelines. Implement and manage end-to-end ML pipelines using: Azure ML (Designer, SDK, Pipelines), Data Factory, and Azure Databricks Vertex AI (Pipelines, Workbench), BigQuery ML, and Dataflow Build and maintain robust MLOps workflows for versioning, retraining, monitoring, and CI/CD using tools like MLflow, Azure DevOps, and GCP Cloud Build. Optimize model performance and inference using techniques like hyperparameter tuning, feature selection, model ensembling, and model distillation. Use and maintain model registries, feature stores, and ensure reproducibility and governance. Collaborate with cloud architects, and software engineers to deliver ML-based solutions. Maintain and monitor model performance in production using Azure Monitor, Prometheus, Vertex AI Model Monitoring, etc. Document ML workflows, APIs, and system design for reusability and scalability. Primary Skills required (Must Have Experience): 5 -7 years of experience in machine learning engineering or applied ML roles. Advanced proficiency in Python, with strong knowledge of libraries such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, TensorFlow, PyTorch. Solid understanding of core ML concepts: supervised/unsupervised learning, cross-validation, bias-variance tradeoff, evaluation metrics (ROC-AUC, F1, MSE, etc.). Hands-on experience deploying ML models using: Azure ML (Endpoints, SDK), AKS, ACI Vertex AI (Endpoints, Workbench), Cloud Run, GKE Familiarity with cloud-native tools for storage, compute, and orchestration: Azure Blob Storage, ADLS Gen2, Azure Functions GCP Storage, BigQuery, Cloud Functions Experience with containerization and orchestration (Docker, Kubernetes, Helm). Strong understanding of CI/CD for ML, model testing, reproducibility, and rollback strategies. Experience implementing drift detection, model explainability (SHAP, LIME), and responsible AI practices. • Strong Python development skills (FastAPI, Pandas, requests, etc.). • Experience working with RESTful APIs, authentication (OAuth, API keys), and pagination. • Knowledge of LLMs and entity extraction techniques using Azure OpenAI or equivalent models. • Experience with prompt engineering and response formatting (JSON, Markdown, tabular). • Familiarity with search engineering concepts: query understanding, result ranking, context optimization. Preferred candidate profile

Primary Skills (Must have hands on Exp): Gen AI, RAG, LLM, Agentic AI, Data Science, Python, AI/ML, API Integration GenAI Expertise: Extensive experience in building Generative AI applications, including RAG, LLM chaining using Langchain, prompt engineering. • Develop Python-based backend services, APIs, and orchestrators that manage tool invocation, context handling, and task decomposition. • Develop goal-oriented autonomous agents capable of planning, decomposing tasks, and invoking tools via APIs and actions. • Performance Optimization: Proven ability to optimize Azure OpenAI models for enhanced performance and scalability. • API Integration: Experience in integrating OpenAI models into software applications using OpenAI APIs. • Documentation: Excellent documentation and communication skills. Role & responsibilities As a Technical Architect with expertise in OpenAI technology, you will play a pivotal role in the design, implementation, and optimization of AI applications and systems. You will collaborate closely with cross-functional teams, software engineers, data scientists, and product managers to ensure the successful deployment of OpenAI technology. Your responsibilities will include: Primary Responsibilities: • AI Solution Design: Lead the design of AI solutions powered by OpenAI technology, defining system architecture and components. • Technical Leadership: Provide technical leadership and guidance to development teams in implementing OpenAI solutions. • OpenAI Model Selection: Identify and recommend the appropriate OpenAI models, such as GPT-3, GPT-4, or specific language models, based on project requirements. • Scalability and Performance: Ensure that AI solutions are scalable and optimized for performance, especially when dealing with large datasets. • API Integration: Integrate OpenAI APIs and SDKs into applications and services, ensuring seamless functionality. • Model Fine-Tuning: Collaborate with data scientists to fine-tune OpenAI models for specific use cases or domains. • Data Processing: Oversee data preprocessing and feature engineering to prepare data for input into OpenAI models. • Security and Compliance: Address security and compliance considerations in OpenAI-powered solutions, particularly when handling sensitive data. • Documentation: Create and maintain technical documentation for OpenAI architectures, model usage, and best practices. • Training and Mentorship: Mentor team members and facilitate knowledge sharing and skill development. • Conduct code reviews and refactoring wherever possible Preferred candidate profile

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. Primary Responsibilities: Work with large, diverse datasets to deliver predictive and prescriptive analytics Develop innovative solutions using data modeling, machine learning, and statistical analysis Design, build, and evaluate predictive and prescriptive models and algorithms Use tools like SQL, Python, R, and Hadoop for data analysis and interpretation Solve complex problems using data-driven approaches Collaborate with cross-functional teams to align data science solutions with business goals Lead AI/ML project execution to deliver measurable business value Ensure data governance and maintain reusable platforms and tools 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: Technical Skills Programming Languages: Python, R, SQL Machine Learning Tools: TensorFlow, PyTorch, scikit-learn Big Data Technologies: Hadoop, Spark Visualization Tools: Tableau, Power BI Cloud Platforms: AWS, Azure, Google Cloud Data Engineering: Talend, Data Bricks, Snowflake, Data Factory Statistical Software: R, Python libraries Version Control: Git Preferred Qualifications: Masters or PhD in Data Science, Computer Science, Statistics, or related field Certifications in data science or machine learning 7+ years of experience in a senior data science role with enterprise-scale impact Experience managing AI/ML projects end-to-end Solid communication skills for technical and non-technical audiences Demonstrated problem-solving and analytical thinking Business acumen to align data science with strategic goals Knowledge of data governance and quality standards 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. #Nic

Primary Responsibilities: Review and resolve complex cases with an end to end mindset to prevent issues or inquiries from recurring. Scope open inventory for like issues for cases worked to group and resolve batches. Demonstrate a knowledge of end-to-end processes of multiple different types of capitated and delegated arrangements within the Value Based Care Model Identify and articulate trends occurring within a risk entity or across multiple risk entities within claims processing and cost share application Identify and articulate trends with our assigned delegates with the Sr. Issue Resolution Analyst and partner to work towards shift left initiatives Partner and collaborate internally and with Risk Entities to correct claims processing and cost share application errors to prevent recurring issues. Actively participate in meetings with cross functional areas aligned by risk entities to share findings Identify and communicate opportunities for improving issue resolution processes, including automation. Clearly document findings and solutions for trended issues after performing root cause analysis Perform reconciliation of member inquiry cases, respond to the specific issue of the inquiry, as well as review for and resolve other issues that may be present for the member, outside of the inquiry Support and communicate with the Sr. Issue Resolution Analyst assigned to your Delegate. Perform root cause and trend analysis of issues by assigned Delegate. Clearly document findings and solutions to prevent future issues Communicate effectively (both written and verbal) with business partners Manages emotions effectively in high-pressure situations, maintaining composure, and fosters a positive work environment conducive to collaboration and productivity 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: Degree or equivalent data science, analysis, mathematics experience Experience supporting operational teams performance with reports and analytics Experience using Word (creating templates/documents), PowerPoint (creation and presentation), Teams, and SharePoint (document access/storage, sharing, List development and management) Basic understanding of reporting using Business Insights tools including Tableau and PowerBI Expertise in Excel (data entry, sorting/filtering) and VBA Proven ability to work across lines of business, claims platforms and on service provider/Delegate issues as needed Proven solid communication skills including oral, written, and organizational skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyoneof every race, gender, sexuality, age, location and incomedeserves 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.

At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Manage the development and deployment of AI and machine learning solutions Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively 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: Bachelors/master degree in computer science, engineering, mathematics, statistics, or a related discipline 12+ years of experience in Software Engineering, Data Science, or Analytics with 8+ years of experience in AI/ML engineering or related fields Experience with cloud platforms and services, such as AWS, Azure, GCP, etc. Experience in developing solutions in the NLP space and relevant projects Hands on Experience in AI and drive the development of innovative AI and machine learning solutions Demonstrated experience in leading and managing AI/ML teams and projects, from ideation to delivery and evaluation Experience with Azure development environments Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Proficient in Python and one of PySpark or Scala. Familiarity with python tools for data processing Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Proficiency in libraries such as Hugging Face and OpenAI API Proven ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts and results to technical and non-technical audiences Proven solid analytical, problem-solving, and decision-making skills, with the ability to balance innovation and pragmatism Proeven passion for learning and staying updated with the latest AI/ML trends and research At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyoneof every race, gender, sexuality, age, location and incomedeserves 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. #njp

Primary Responsibilities: Reporting Development and Data Integration : Assist with data projects related to integration with our core claims adjudication engines, eligibility, and other database items as necessary Support the data leads by producing ad hoc reports as needed based on requirements from the business Report on key milestones to our project leads Ensuring all reporting aligns with brand standards Ensuring PADU guidelines for tools, connections, and data security Build a network with internal partners to assist with validating data quality Analytical Skills Utilization : Applying analytical skills and developing business knowledge to support operations Identify automation opportunities through the trends and day to day tasks to help create efficiencies within the team Perform root cause analysis via the 5 why root causing to identify process gaps and initiate process improvement efforts Assist with user testing for reports, business insights dashboards, and assist with automation validation review 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: Degree or equivalent data science, analysis, mathematics experience Experience supporting operational teams performance with reports and analytics Experience using Word (creating templates/documents), PowerPoint (creation and presentation), Teams, and SharePoint (document access/storage, sharing, List development and management) Basic understanding of reporting using Business Insights tools including Tableau and PowerBI Expertise in Excel (data entry, sorting/filtering) and VBA Proven solid communication skills including oral, written, and organizational skills Proven ability to manage emotions effectively in high-pressure situations, maintaining composure, and fosters a positive work environment conducive to collaboration and productivity Preferred Qualifications: Experience leveraging and creating automation such as macros, PowerAutomate, Alteryx/ETL Applications Experience working with cloud-based servers, knowledge of database structure, stored procedures Experience performing root cause analysis and demonstrated problem solving skills Knowledge of R/Python, SQL, DAX or other coding languages Knowledge of multiple lines of business, benefit structures and claims processing systems At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyoneof every race, gender, sexuality, age, location and incomedeserves 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.

Data Science Consultants (DSCs) design, develop and execute high-impact analytics solutions for large, complex, structured and unstructured data sets (including big data) to help clients make better fact-based decisions. Responsibilities: Develop advanced algorithms that solve problems of large dimensionality in a computationally efficient and statistically effective manner Execute statistical and data mining techniques (e.g. hypothesis testing, machine learning and retrieval processes) on large data sets to identify trends, figures and other relevant information Collaborating with clients and cross functional teams to develop & deploy the data science solutions effectively & communicate the analysis findings Contribute to the evaluation of emerging datasets and technologies that may contribute to our analytical platform Evaluating emerging datasets and technologies that may contribute to our analytical platform Owning the development of select assets/accelerators for efficient scaling of capability Contributing to the thought leadership of the firm by helping in researching the evolving topics and publishing them Qualifications: Bachelor's or master's degree or PhD in Computer Science (or Statistics) from a premier institute, and strong academic performance with analytic and quantitative coursework is required; Knowledge of big data/advanced analytics concepts and algorithms (e.g. text mining, social listening, recommender systems, predictive modeling, etc.); Knowledge of programming (e.g. Java/Python/R); Exposure to tools/platforms (e.g. Hadoop eco system and database systems); Excellent oral and written communication skills; Strong attention to detail, with a research-focused mindset; Excellent critical thinking and problem-solving skills;

We are looking for an experienced MLOps Manager with a proven track record of leading teams in designing, building, and managing machine learning infrastructure and pipelines in on-premises environments. The ideal candidate will bring 9+ years of experience in DevOps / MLOps, including hands-on leadership in delivering multiple end-to-end MLOps projects. You will oversee the MLOps function, enabling scalable, secure, and efficient ML operations, while collaborating closely with Data Science, IT, and Engineering teams. Key Responsibilities Lead the design, development, and management of robust ML pipelines and infrastructure in on-premises or private cloud environments. Define and drive MLOps strategy and best practices for model deployment, monitoring, and lifecycle management. Oversee the implementation and governance of Infrastructure as Code (IaC) using tools like Ansible, Terraform (for private cloud), or Puppet. Manage, mentor, and guide MLOps engineers, fostering a high-performing and collaborative team. Collaborate with cross-functional teams to align MLOps solutions with business and data science objectives. Drive automation and standardization of CI/CD pipelines, model versioning, and container orchestration (e.g., Docker, Kubernetes, OpenShift). Ensure comprehensive documentation of infrastructure, architecture, and operational workflows using tools like Confluence, GitHub Wikis, and system diagrams. Identify and implement optimization opportunities for ML infrastructure performance, cost, and scalability. Stay updated on industry trends and emerging technologies to continuously enhance MLOps capabilities. 9+ years of experience in DevOps / MLOps with at least 4 years in a leadership or managerial role. Demonstrated success in delivering multiple MLOps projects in on-premises or private cloud environments.

Software Development Engineer III Back to job search results Tesco India Bengaluru Hybrid Full-Time Apply by 20-Jun-2025 About the role Refer you will be responsible section What is in it for you At Tesco, we are committed to providing the best for you. As a result, our colleagues enjoy a unique, differentiated, market- competitive reward package, based on the current industry practices, for all the work they put into serving our customers, communities and planet a little better every day. Our Tesco Rewards framework consists of pillars - Fixed Pay, Incentives, and Benefits. Total Rewards offered at Tesco is determined by four principles - simple, fair, competitive, and sustainable. Salary - Your fixed pay is the guaranteed pay as per your contract of employment. Leave & Time-off - Colleagues are entitled to 30 days of leave (18 days of Earned Leave, 12 days of Casual/Sick Leave) and 10 national and festival holidays, as per the companys policy. Making Retirement Tension-FreeSalary - In addition to Statutory retirement beneets, Tesco enables colleagues to participate in voluntary programmes like NPS and VPF. Health is Wealth - Tesco promotes programmes that support a culture of health and wellness including insurance for colleagues and their family. Our medical insurance provides coverage for dependents including parents or in-laws. Mental Wellbeing - We offer mental health support through self-help tools, community groups, ally networks, face-to-face counselling, and more for both colleagues and dependents. Financial Wellbeing - Through our financial literacy partner, we offer one-to-one financial coaching at discounted rates, as well as salary advances on earned wages upon request. Save As You Earn (SAYE) - Our SAYE programme allows colleagues to transition from being employees to Tesco shareholders through a structured 3-year savings plan. Physical Wellbeing - Our green campus promotes physical wellbeing with facilities that include a cricket pitch, football field, badminton and volleyball courts, along with indoor games, encouraging a healthier lifestyle. You will be responsible for My impact reaches across the team in which I work. I provide technical leadership of medium to large features; participating in their design and taking accountability for their delivery. I am comfortable implementing and shipping end-to-end stories and am starting to understand the deeper problems in my part of the business. I am likely to be considered an expert in a specific part of my domain. This is the first level at which I do more than complete the work thats been assigned to me: I am starting to build and prioritise my own work by understanding the problems my team faces and proposing; implementing; and delivering solutions to them. I am aware of the short-term and long-term goals across my product. I work within my team; utilising data driven decision making techniques; to encouraging optimal outcomes whilst accepting appropriate trade-offs. I am comfortable both supporting other engineers in their delivery and taking the lead on major components or small services as appropriate. At this level I display a degree of ownership for the work conducted by the team and am experienced enough to know when I need support. I am able to identify risks and raise these as appropriate. At this level I am beginning to support; coach; and mentor those around me. As junior engineers join the team; I am assisting them through their onboarding process and leaning on my past experience to help get them up to speed. Whilst I may not formally be a mentor for other engineers; I am someone that individuals across the team will come to for advice and help. I prioritise sharing skills and technical knowledge across my team. I contribute to the raising the quality bar of my teams codebase; both in the code that I produce and by helping to peer review code written by other team members. I proactively provide constructive and useful feedback to other team members on their code. I have a good understanding of best practices across the industry and of Tesco architectural standards. I make sure to put these principles and standards into practice when completing my work. I am aware of the best testing and deployment strategies in the industry and have a view on the suitability of implementing these within my team. I am comfortable working in a group context and am capable of communicating technical concepts to key stakeholders. You will need Refer you will be responsible section About us Tesco in Bengaluru is a multi-disciplinary team serving our customers, communities, and planet a little better every day across markets. Our goal is to create a sustainable competitive advantage for Tesco by standardising processes, delivering cost savings, enabling agility through technological solutions, and empowering our colleagues to do even more for our customers. With cross-functional expertise, a wide network of teams, and strong governance, we reduce complexity, thereby offering high-quality services for our customers. Tesco in Bengaluru, established in 2004 to enable standardisation and build centralised capabilities and competencies, makes the experience better for our millions of customers worldwide and simpler for over 3,30,000 colleagues Tesco Technology Today, our Technology team consists of over 5,000 experts spread across the UK, Poland, Hungary, the Czech Republic, and India. In India, our Technology division includes teams dedicated to Engineering, Product, Programme, Service Desk and Operations, Systems Engineering, Security & Capability, Data Science, and other roles. At Tesco, our retail platform comprises a wide array of capabilities, value propositions, and products, essential for crafting exceptional retail experiences for our customers and colleagues across all channels and markets. This platform encompasses all aspects of our operations - from identifying and authenticating customers, managing products, pricing, promoting, enabling customers to discover products, facilitating payment, and ensuring delivery. By developing a comprehensive Retail Platform, we ensure that as customer touchpoints and devices evolve, we can consistently deliver seamless experiences. This adaptability allows us to respond flexibly without the need to overhaul our technology, thanks to the creation of capabilities we have built. Apply

Working at Atlassian Atlassians can choose where they work - whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. ","responsibilities":" Responsibilities Your future team Transformations AI foundations is a core pillar inside the DevInfra org. Its purpose is to build AI-powered developer productivity tools for internal and external customers. What you ll do As an associate Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality into various tools/platform. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. ","qualifications":" Qualifications On the first day, well expect you to have Bachelors or Masters degree (preferably a Computer Science degree or equivalent experience). 1+ years of related industry experience in the data science domain. Familiarity in Python/Java/Golang/Typescript with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, GCloud, Databricks). Familiarity with LLMs (prompt engineering, RAG), AirFlow, MLFlow, model inferencing, ONNX pipelines will be preferred. Great verbal and written communication skills along with the ability to explain complex data science and ML concepts to diverse audiences. Ability to craft compelling stories with data. Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of having something nowvs perfection sometime in the future. Agile development mindset, appreciating the benefit of constant iteration and improvement. Preference for folks who have worked prior in remote and/or hybrid environments. Our perks benefits Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit

Assistant Professor - Data Science Conduct lectures, practicals, and tutorials as per timetable. Develop course materials, lab manuals, and teaching plans. Use effective teaching methodologies and ICT tools. Assess and evaluate student performance regularly. Act as mentor for student batches. Guide UG project work and internships. Support students in academic and career counselling. Participate in syllabus implementation and feedback. Contribute to question paper setting, evaluation, and result analysis. Maintain academic records and course files. Engage in research activities and paper publication. Attend FDPs, seminars, conferences, and workshops. Apply for minor research projects or funding opportunities. Assist in organizing departmental events, seminars, and technical activities. Participate in admission counselling, examination duties, and academic audits. Contribute to NAAC/NBA-related documentation and quality initiatives. Participate in Student Monitoring System/LG System. Publish research papers in peer-reviewed journals (SCI/Scopus/WOS/UGC-listed). Coordinate in Student Monitoring System/LG System. Actively engage in the Student Monitoring System and LG system. Support institutional activities related to SAP SLCM and MIS. Encourage students to maintain discipline and cleanliness in the department. Any other responsibilities as may be assigned to you by the Principal/Management from time to time

Senior Analyst, Data Science Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound social impact as a Senior Analyst on our Data Science Team in Bangalore and Gurgaon. What you ll achieve Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods, and models. What s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data You will: Interact with business stakeholders, product managers, software engineers, data engineers, and data analysts to create data science products Write SQL queries, python scripts to clean, wrangle data from multiple sources making them model ready Use techniques which includes (but not limited to) Natural Language Processing, Machine Learning, Gen AI, Data Pipelining to build scalable models Build Data Pipelines & platform to operationalize the models at scale Become a subject matter expert of the data to create and refine features for modeling Take the first step towards your dream career Every Dell Technologies team member brings something unique to the table. Here s what we are looking for with this role: Essential Requirements Requires 2 + years of related experience in a professional role with a bachelor s degree; or 1 + years with a master s degree. Solid programming skills to retrieve, analyze and process data, and build machine learning models from the ground up (Python/R) Data Science Platforms like Domino Data Lab, Apache Airflow, AWS, and Google Cloud (working environment to build and deploy models) Machine Learning techniques like Ranking, Classification, Clustering, Regression and Topic Modeling , Deep learning, Neural networks and GEN AI Deep knowledge of machine learning, information retrieval, data mining, statistics, NLP, or related field Application closing date: 17th July 2025

We are in search of a Machine Learning Engineer with proficient work experience in the field This role will play a pivotal role in shaping the projects through cutting-edge machine learning techniques You will have the opportunity to lead impactful projects, solving complex problems and data driven decision making If you are an experienced individual with a passion for Machine Learning and ready for its new advancements , we invite you to be an integral part of our team ## The responsibilities of the job are given below:- Collaborate with cross functional teams to understand the project requirements Thorough understanding and research of the business or project requirements for proving the best solution - Architecting verification IP and full verification environments with verification delivery ownership - Investigating and scripting new verification flows and optimizing existing ones- Analysis of data from simulation runs using machine learning and data science techniques to drive efficient bug discovery and debug- Developing methodology and deploying within the group and having full ownership of verification closure and mentoring other members of the team - Close collaboration with other Arm engineering teams leading to high quality IP that works well in a complete system ## Qualification:- Team Player- Proven work experience- Logical and analytical thinker- Adaptive to technical advancements