554 Predictive Modeling Jobs - Page 19

Lead analytics Team from scoping to delivery and solve business problems through basic to advanced analytics Proactively propose, initiate, independently execute and own strategic strategic ideas and POCs targeting revenue growth & larger business Required Candidate profile Exp of SAS, SQL, Python (Mandate) exp in BFSI Domain only Ability to work effectively in a team environment Strong communication and interpersonal skills Knowledge of MS Office PowerPoint, Excel

Role & responsibilities Develop and optimize Oracle PL/SQL queries to extract and manipulate data based on business requirements. Design and implement waterfall models for campaign analytics using Oracle PL/SQL. Leverage Python to build predictive models. Work on collaborative analytics to enhance campaign effectiveness. Capture dynamic business user inputs, create predefined queries, and ensure data accuracy for real-time decision-making. Ensure best practices in data modeling, ETL, and performance tuning in an Exadata-based Data Warehouse (DWH) environment. Preferred candidate profile Experienced in Oracle PL/SQL, Python, and Data Analytics. Proficiency in ETL processes, data warehousing, and query performance optimization. Hands-on experience in predictive modeling, machine learning concepts, and statistical analysis using Python. Strong problem-solving, analytical thinking, and communication skills. Experience in banking or financial services domains. Prior work in a Data Warehouse (DWH) environment on Exadata. Familiarity with big data technologies and data visualization tools is a plus.

About The Role Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions. ? Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options 3. Team Management a. Talent Management i. Support on boarding and training to enhance capability & effectiveness ? Deliver No. Performance Parameter Measure 1. Demand generation # PoC supported 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management # Skills acquired ? ? Mandatory Skills: AI Cognitive. Experience3-5 Years. 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.

About The Role Job Role & Responsibility/Designation Quality and Process Excellence Consultant ? Delivery Process/ Function Name Quality ? Educational Qualification B.Sc. / BE / B Tech/ MBA/ B.Stat ? Skills ( Must Have) Problem solving tools/ analytical skills Excellent communication / interpersonal, facilitation skills High energy level, confident, assertive and team player ? Experience ( Minimum) Functional knowledge of Six Sigma, Statistical tools, Quality & Process re-engineering Exposure to ISO, CMMi or COPC will be added advantage Consulting experience in Shared Services Set up/BPO space is desirable Mandatory Skills: Process Advisory. Experience5-8 Years. 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.

About The Role Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions ? Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team ? Deliver No. Performance Parameter Measure 1. Demand generation Order booking 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management % trained on new skills, Team attrition % ? ? Mandatory Skills: Python for Data Science. Experience8-10 Years. 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.

About The Role Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions ? Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT to evaluate ML deployment options c. Integrate model performance management tools into the current business infrastructure 3. Team Management a. Resourcing i. Support recruitment process to on-board right resources for the team b. Talent Management i. Support on boarding and training for the team members to enhance capability & effectiveness ii. Manage team attrition c. Performance Management i. Conduct timely performance reviews and provide constructive feedback to own direct reports ii. Be a role model to team for five habits iii. Ensure that the Performance Nxt is followed for the entire team d. Employee Satisfaction and Engagement i. Lead and drive engagement initiatives for the team ? Deliver No. Performance Parameter Measure 1. Demand generation Order booking 2. Revenue generation through delivery Timeliness, customer success stories, customer use cases 3. Capability Building & Team Management % trained on new skills, Team attrition % ? ? Mandatory Skills: Data Science. Experience5-8 Years. 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.

About the role: We are seeking a highly skilled Domain Expert in Condition Monitoring to join our team and play a pivotal role in advancing predictive maintenance strategies for electrical equipment. This position focuses on leveraging cutting-edge machine learning and data analytics techniques to design and implement scalable solutions that optimize maintenance processes, enhance equipment reliability, and support operational efficiency. As part of this role, you will apply your expertise in predictive modeling, supervised and unsupervised learning, and advanced data analysis to uncover actionable insights from high-dimensional datasets. You will collaborate with cross-functional teams to translate business requirements into data-driven solutions that surpass customer expectations. If you have a passion for innovation and sustainability in the industrial domain, this is an opportunity to make a meaningful impact. Key Responsibilities: Develop and implement predictive maintenance models using a variety of supervised and unsupervised learning techniques. Analyze high-dimensional datasets to identify patterns and correlations that can inform maintenance strategies. Utilize linear methods for regression and classification, as well as advanced techniques such as splines, wavelets, and kernel methods. Conduct model assessment and selection, focusing on bias, variance, overfitting, and cross-validation. Apply ensemble learning techniques, including Random Forest and Boosting, to improve model accuracy and robustness. Implement structured methods for supervised learning, including additive models, trees, neural networks, and support vector machines. Explore unsupervised learning methods such as cluster analysis, principal component analysis, and self-organizing maps to uncover insights from data. Engage in directed and undirected graph modeling to represent and analyze complex relationships within the data. Collaborate with cross-functional teams to translate business requirements into data-driven solutions. Communicate findings and insights to stakeholders, providing actionable recommendations for maintenance optimization. Mandatory Requirements: Master"™s degree or Ph.D. in Data Science, Statistics, Computer Science, Engineering, or a related field. Proven experience in predictive modeling and machine learning, particularly in the context of predictive maintenance. Strong programming skills in languages such as Python, R, or similar, with experience in relevant libraries (e.g., scikit-learn, TensorFlow, Keras). Familiarity with data visualization tools and techniques to effectively communicate complex data insights. Experience with big data technologies and frameworks (e.g., Hadoop, Spark) is a plus. Excellent problem-solving skills and the ability to work independently as well as part of a team. Strong communication skills, with the ability to convey technical concepts to non-technical stakeholders. Good to Have: Experience in Industrial software & Enterprise solutions Preferred Skills & Attributes: Strong understanding of modern software architectures and DevOps principles. Ability to analyze complex problems and develop effective solutions. Excellent communication and teamwork skills, with experience in cross-functional collaboration. Self-motivated and capable of working independently on complex projects. About the Team Become a part of our mission for sustainabilityclean energy for generations to come. We are a global team of diverse colleagues who share a passion for renewable energy and have a culture of trust and empowerment to make our own ideas a reality. We focus on personal and professional development to grow internally within our organization. Who is Siemens Energy? At Siemens Energy, we are more than just an energy technology company. We meet the growing energy demand across 90+ countries while ensuring our climate is protected. With more than 96,000 dedicated employees, we not only generate electricity for over 16% of the global community, but we"™re also using our technology to help protect people and the environment. Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.

Overview PepsiCo is embarked on a significant initiative of digitalization and standardization of the FP&A solution across all its divisions to make the finance organization more Capable, more Agile, and more Efficient. The MOSAIC program is a key enabler of that vision. It is the FP&A solution of the PepsiCo Global Template (PGT) that, for the first time, aims to integrate vertical planning for Business Units (BUs) or markets, and horizontal planning for functions (e.g., Global Procurement, Compensation and Benefits, etc.) that have accountability across markets. The program aims to harmonize data, planning processes and ways of working across PepsiCo organization. The Sustain Team for MOSAIC Solution is responsible for the delivery of high-quality break fixes and keep stability for the Mosaic markets which are live. Also, to ensure zero minimum critical incident from Production, coordinate and minimize the downtimes of Prod and non-Prod environments. The overall solution should be managed closely with our Business Support (Center of Excellence), various business teams (product owners and market teams) and other application support teams. The role will interact directly on the design/development of incident break fixes and maintenance of the solution and will have to work closely with the various detail design & development teams. This role will require a strong background in technical solutions which are part of Mosaic architecture such as TM1, Alteryx, Data Lake Responsibilities The candidate needs to have a high degree of initiative to work independently and get things done in a complex matrix organization. K ey Accountabilities Includes following for Mosaic Solution Handle Incidents for Mosaic solution and strive for resolution of incidents within SLA. Subject matter expert (SME), responsible for resolving incidents and for continuous communication about incident status. Act as a resolver and communicate with the customer as required. Member of a technical, operations and application management team. Monitor the teams tickets queue for his service, self-assign tickets to him or directly work on tickets assigned by the Service Controller. Responsible for forwarding tickets that require a change to the Service Controller and manage the Change Management process for break fixes implementation. Handle tickets escalations to the Service Controller. Qualifications Key Skill Required University education (BS /BA level) or equivalent work experience 6+ Year of experience in Alteryx Minimum of 8+ years of Information Technology or business experience Strong knowledge of Data Modelling Technical Skills Alteryx Designer SQL, MySQL Python Tableau Data Analysis, Predictive Modelling, Forecasting ODBC driver SAP & Oracle exposure Service Now, Jira or other ticketing tools Non-Technical Skills Strong development background with minimum 5 years experience in Sustain teams (offshore mainly) on business solutions projects with process flow, data flow and integration as a critical component. Knowledge of ITIL methodology. Team Management. Understanding of the Financial Closing and Forecasting process. Strong Interpersonal and Communication skills. Good verbal and written Communication. Strong Stakeholder management. Knowledge of Project Management. Portfolio Management. Self-motivation and ability to stay focused.

Overview PepsiCo is embarked on a significant initiative of digitalization and standardization of the FP&A solution across all its divisions to make the finance organization more Capable, more Agile, and more Efficient. The MOSAIC program is a key enabler of that vision. It is the FP&A solution of the PepsiCo Global Template (PGT) that, for the first time, aims to integrate vertical planning for Business Units (BUs) or markets, and horizontal planning for functions (e.g., Global Procurement, Compensation and Benefits, etc.) that have accountability across markets. The program aims to harmonize data, planning processes and ways of working across PepsiCo organization. The Sustain Team for MOSAIC Solution is responsible for the delivery of high-quality break fixes and keep stability for the Mosaic markets which are live. Also, to ensure zero minimum critical incident from Production, coordinate and minimize the downtimes of Prod and non-Prod environments. The overall solution should be managed closely with our Business Support (Center of Excellence), various business teams (product owners and market teams) and other application support teams. The role will interact directly on the design/development of incident break fixes and maintenance of the solution and will have to work closely with the various detail design & development teams. This role will require a strong background in technical solutions which are part of Mosaic architecture such as TM1, Alteryx, Data Lake. Responsibilities The candidate needs to have a high degree of initiative to work independently and get things done in a complex matrix organization. Key Accountabilities Includes following for Mosaic SolutionIBM Planning Analytics Cloud / Alteryx / Data Lake Handle Incidents for Mosaic solution and strive for resolution of incidents within SLA. Subject matter experts (SMEs), responsible for resolving incidents and for continuous communication about incident status. Act as a resolver and communicate with the customer as required. He is a member of a technical, operations, or application management team or supplier. Monitor the teams tickets queue for his service, self-assign tickets to him or directly work on tickets assigned by the Service Controller. Responsible for forwarding tickets that require a change to the Service Controller and manage the Change Management process for break fixes implementation. Handle tickets escalations to the Service Controller. Qualifications Key Skill Required University education (BS /BA level) or equivalent work experience 4+ years of experience in Alteryx 6+ years of Information Technology Technical Skills Alteryx Designer SQL, MySQL Python Tableau Data Analysis, Predictive Modelling, Forecasting ODBC driver SAP & Oracle exposure Service Now, Jira or other ticketing tools Non-Technical Skills Strong development background with minimum 5 years experience in Sustain teams (offshore mainly) on business solutions projects with process flow, data flow and integration as a critical component. Knowledge of ITIL methodology. Understanding of the Financial Closing and Forecasting process. Strong Interpersonal and Communication skills. Good verbal and written Communication. Strong Stakeholder management. Knowledge of Project Management. Self-motivation and ability to stay focused.

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries- Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must.- Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch)- Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus.- Proficient knowledge of cloud platforms (AWS, GCP, Azure).- Strong problem-solving and analytical skills.- Ability to work in team-oriented, collaborative environment. Data Scientist- Statistician- Data Engineer- Python- R- Supervised & Unsupervised learning- Machine Learning Algorithms- Deep Learning- Hugging Face- Natural Language Processing (NLP)- Computer Vision- TensorFlow- PyTorch- Scikit-learn- Transformers- LLM Frameworks- LLM Models- GPT -3, 4o- BERT- Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries- Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch)- Experience with data labeling and annotation tools.- Certifications in cloud platforms or ML technologies can be a plus.- Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills.- Ability to work in team-oriented, collaborative environment. Data Scientist- Statistician- Data Engineer- Python- R- Supervised & Unsupervised learning- Machine Learning Algorithms- Deep Learning- Hugging Face- Natural Language Processing (NLP)- Computer Vision- TensorFlow- PyTorch- Scikit-learn- Transformers- LLM Frameworks- LLM Models- GPT -3, 4o- BERT- Llama

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 relevantinformation 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 toour 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; High motivation, good work ethic and maturity. ZS is a global consulting firm; fluency in English is required, additional fluency in at least one European or Asian language is desirable. ZS offers a competitive compensation package with salary and bonus incentives, plus an attractive benefits package.

Visa Inc. is seeking a highly skilled Data Engineer to join our Data Analytics team. The ideal candidate will possess strong data engineering skills, analytical domain knowledge, and experience with Google Analytics data, GA4 behavioral data pipelines, and Google BigQuery. Additionally, the candidate should have knowledge of Generative AI (GenAI) frameworks, a keen interest in exploring automation opportunities in the data engineering domain, and a solid understanding of dealing with big data and querying it effectively. This role will be pivotal in developing and maintaining data pipelines and analytical solutions to enhance our digital presence and improve customer engagement. Responsibilities: Design, develop, and implement data integration and analytics solutions using Google Analytics data and Google BigQuery. Architect and maintain scalable data pipelines for GA4 behavioral data, ensuring data quality and integrity. Collaborate with cross-functional teams to gather requirements and deliver data-driven business solutions. Perform data cleaning, transformation, and analysis to provide actionable insights. Develop and maintain ETL processes using technologies such as Hadoop, Hive, Spark, and SQL. Optimize data queries and manage data storage solutions to support advanced analytics. Implement best practices for data engineering and ensure compliance with data governance policies. Explore and implement automation opportunities in data engineering using GenAI frameworks. Provide technical support and troubleshooting for data-related issues. Handle large-scale data processing and querying using tools like Google BigQuery, ensuring efficient data retrieval and analysis. This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager. Basic Qualifications 2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Preferred Qualifications Bachelors degree in Computer Science, Information Technology, or a related field.

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Job Title Senior Research Scientist (Hybrid) Job Description For more than 80 years, Kaplan has been a trailblazer in education and professional advancement. We are a global company at the intersection of education and technology, focused on collaboration, innovation, and creativity to deliver a best in class educational experience and make Kaplan a great place to work. Our offices in India opened in Bengaluru in 2018. Since then, our team has fueled growth and innovation across the organization, impacting students worldwide. We are eager to grow and expand with skilled professionals like you who use their talent to build solutions, enable effective learning, and improve students lives. The future of education is here and we are eager to work alongside those who want to make a positive impact and inspire change in the world around them. Kaplan is looking for a Senior Research Scientist to join the Learning Analytics and Psychometrics team. This global team consists of talented professionals who provide their services in the field of psychometrics and learning analytics. This team enables proper assessment and learning functioning across all product lines and is responsible for learning and testing algorithms, within the Kaplan ecosystem. The Senior Research Scientist will be responsible for the projects related to learning analytics, which analyzes learner s activity, learning and assessment data. The role will be proficient with analyzing large and complex datasets, and transforming data into actionable insights and suggesting strategies to improve learners learning experience and performance. The Senior Research Scientist role is a creative problem solver who utilizes advanced statistical principles and modeling techniques to uncover new insights that will significantly and meaningfully impact student s learning. The position requires an experienced, highly motivated, self-driven and creative individual, with strong critical thinking and problem solving skills, able to multi-task independently with minimum supervision. Primary Responsibilities Work closely with the Director of Psychometrics and Learning Analytics on the assessment and learning analytic projects. Independently design, plan, and execute complex learning analytical projects which are aimed to improve students experience and outcome in online learning. Independently perform the full range of learning analytics activities including descriptive analytics, predictive analytics, data mining, causal inference, machine learning, network analysis, and analytic dashboards. Extract, preprocess, manipulate, analyze & interpret complex data from various corporate data sources developing advanced analytic algorithms and solutions, deriving key observations, findings, insights, and formulating actionable recommendations Apply advanced analytical and research methods and incorporate AI models to identify learning gain, model learner s behaviors, develop learning metrics, recommend learning paths, and improve learning product effectiveness. Collaborate with psychometricians, data analysts, data scientists, content developers, platform engineers, product and business owners, and other stakeholders to solve product and business problems. Prepares technical reports, whitepapers, and related documents. Present impact, insights, outcomes & recommendations to key business partners and stakeholders. Mentor junior team members and provide guidance on project directions and technical challenges. Other duties as assigned. Minimum Qualifications Advanced Degree (Master s or Doctoral) in Data Science, Statistics, Quantitative methodology, Educational Technology, Mathematics, Computer Science, Psychometrics or a related field with strong quantitative focus PhD candidates are preferred and strongly recommended 5 + years of work experience in data science, analytics, statistical modeling or quantitative research in an educational and/or professional organization. Substantial work experience in educational research and learning analytics is a plus. Hands-on experience with educational assessment and learning analytical data and research projects. Proficient in R/ Python or one programming language. Proficient in data manipulation and applied statistics including multiple regression, predictive modeling, Bayesian methods, and machine learning. Excellent working knowledge of SQL and data visualization tools. Excellent verbal, written, and interpersonal communication skills. Experience in leading research projects and providing guidance to junior members. Preferred Qualifications Experience of AI in educational learning products, including adaptive learning and individualized tutoring, is a big plus.

About The Role : Job TitleModel Validation Lead- Derivative Pricing Corporate TitleVP LocationMumbai, India Role Description Model Risk Managements mission is to manage, independently and actively, model risk globally in line with the bank's risk appetite with responsibility for: Performing robust independent model validation; Ensuring early and proactive identification of Model Risks; Designing and recommending Model Risk Appetite; Effectively managing and mitigating Model Risks; Establishing Model Risk metrics; Designing and implementing a strong Model Risk Management and governance framework; Creating bank-wide Market Risk policies The Pricing Model Validation team as part of MoRM is responsible for the independent review and analysis of all derivative pricing models used for valuation and pricing across the bank. What we'll offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities The role is to independently review and analyse derivative models for pricing and risk management across Rates, FX and Hybrids. The role as a Quantitative Analyst in Mumbai will work closely with the pricing validation team in London and Berlin to produce, analyse and document validation testing. Reviews and analysis require a good understanding of the mathematical models used, implementation methods, products traded in these markets, and the associated risks. The outcome of review and analysis and independent implementation will form the basis of discussion with key model stakeholders includingFront Office Trading; Front Office Quants; Market Risk Managers; and Finance Controllers. Your skills and experience Excellent mathematical ability with an understanding of Stochastic Calculus, Partial Differential Equations, Monte-Carlo Methods, Finite Difference Methods, and Numerical Algorithms. Strong interest in financial markets (especially derivative pricing) demonstrated by qualifications and/or experience. Experience coding in Python an advantage. Excellent communication skills both written and oral. Education/Qualifications Academic degree in a quantitative discipline (e.g. Mathematical Finance / Statistics, Maths, Physics, Engineering) with a focus on application. How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

About The Role : Job Title: Analytics Senior Analyst LocationJaipur, India Corporate TitleAVP Role Description You will be joining the Data & Analytics team as part of the Global Procurement division. The teams purpose is: Deliver trusted third-party data and insights to unlock commercial value and identify risk Develop and execute the Global Procurement Data Strategy Deliver the golden source of Global Procurement data, analysis and insights via dbPi, our Tableau self-service platform, leveraging automation and scalability on Google Cloud Provide data and analytical support to Global Procurement prioritised change initiatives The team leverages several tools and innovative techniques to create value added insights for stakeholders across end-to-end Procurement processes including, but not limited to, Third party Risk, Contracting, Spend, Performance Management, etc. What we'll offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities You develop a sound understanding of the various tools and entire suite of analytical offerings on the standard procurement insights platform called dbPi. You support our stakeholders by understanding their requirements, challenge appropriately where needed in order to scope the porblem conceptualizing the optimum approach, and developing solutions using appropriate tools and visualisation techniques. You are comfortable leading small project teams in delivering the analytics change book of work, keeping internal and external stakeholders updated on the project progress while driving forward the key change topics For requests which are more complex in nature, you connect the dots and come up with a solution by establishing linkages across different systems and processes. You take end to end responsibility for any change request in the existing analytical product / dashboard starting from understanding the requirement, development, testing, QA and finally deliver it to stakeholders to their satisfaction. You are expected to deliver automation and Clean Data initiatives like deployment of Rules engine, Data quality checks enabled through Google cloud, bringing in Procurement data sources into GCP. You act as a thought partner to the Chief Information Offices deployment of Google Cloud Platform to migrate the data infrastructure layer (ETL processes) currently managed by Analytics team. You should be able to work in close collaboration with cross-functional teams, including developers, system administrators, and business stakeholders. Your skills and experience We are looking for talents with a Degree (or equivalent) in Engineering, Mathematics, Statistics, Sciences from an accredited college or university (or equivalent) to develop analytical solutions for our stakeholders to support strategic decision making. Any professional certification in Advanced Analytics, Data Visualisation and Data Science related domain is a plus. You have a natural curiosity for numbers and have strong quantitative & logical thinking skills. You ensure results are of high data quality and accuracy. You have working experience on Google Cloud and have worked with Cross functional teams to enable data source and process migration to GCP, you have working experience with SQL You are adaptable to emerging technologies like leveraging Machine Learning and AI to drive innovation. Procurement experience (useful --- though not essential) across vendor management, sourcing, risk, contracts and purchasing preferably within a Global and complex environment. You have the aptitude to understand stakeholders requirements, identify relevant data sources, integrate data, perform analysis and interpret the results by identifying trends and patterns. You enjoy the problem-solving process, think out of the box and break down a problem into its constituent parts with a view to developing end-to-end solution. You display enthusiasm to work in data analytics domain and strive for continuous learning and improvement of your technical and soft skills. You demonstrate working knowledge of different analytical tools like Tableau, Databases, Alteryx, Pentaho, Looker, Big Query in order to work with large datasets and derive insights for decision making. You enjoy working in a team and your language skills in English are convincing, making it easy for you to work in an international environment and with global, virtual teams How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs

About The Role : Job TitleEngineer, AVP LocationPune, India Role Description The candidate in this role will architect, design, develop application code, implement technical solutions, and configure applications in different environments in response to business problems. To meet the requirements of the business, the candidate will actively participate in architecture design, application development lifecycle, investigate issues (bugs/performance), propose solutions, promote re-usability of existing components, and contribute to the creation of frameworks. The candidate will assist junior members of the team and guide them as applicable. Knowledge of Trade finance domain will be an advantage. What we'll offer you As part of our flexible scheme, here are just some of the benefits that youll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Support business and key stakeholders to make data-driven decisions Work with the team on AI/ML solutions to improve the efficiency of various Trade Finance products Support with the migration of existing ML workflow to GCP using products such as DocAI Your skills and experience Experience using common languages used in data science preferably Python Experience in Google Doc AI, Gemini or other state-of-the-art LLMs is necessary Knowledge of AI/ML concepts beneficial - especially Natural Language Processing, Document Understanding and Computer Vision Knowledge of common frameworks like numpy, sklearn, pandas, tensorflow Familiarity with agile software development practices Desire to learn and adapt to new technology Strong analytical skills, with a university degree in Computer Science, Data Science, Mathematics, Physics or similar How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Role : Principal Data Scientist / LLM Specialist Responsibilities : Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question answering is must. Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) Experience with data labeling and annotation tools. Certifications in cloud platforms or ML technologies can be a plus. Proficient knowledge of cloud platforms (AWS, GCP, Azure). Strong problem solving and analytical skills. Ability to work in team oriented, collaborative environment.Keywords : Data Scientist Statistician Data Engineer Python R Supervised & Unsupervised learning Machine Learning Algorithms Deep Learning Hugging Face Natural Language Processing (NLP) Computer Vision TensorFlow PyTorch Scikit learn Transformers LLM Frameworks LLM Models GPT 3, 4o BERT Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

: Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

You'll be Responsible for: Design, develop and implement cutting-edge AI/ML solutions, including Large Language Models (LLMs) and Generative AI applications Lead projects end-to-end while mentoring team members in AI-ML, including traditional ML and emerging AI technologies Drive innovation in AI agent development and orchestration for automated decision-making systems Establish best practices for responsible AI development and deployment What you'd have: AI-ML Engineer or Data Scientist with 3 11 years of relevant experience Strong expertise in modern AI frameworks and tools: ML/DL frameworks (TensorFlow, PyTorch, Keras, Sklearn) LLM frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) Vector databases (Pinecone, Weaviate, ChromaDB) – Good To Have Hands-on experience with: Generative AI and foundation models Prompt engineering and LLM fine-tuning AI agent development and orchestration RAG (Retrieval-Augmented Generation) systems Proven experience in data preparation, including: Advanced data preprocessing techniques Feature engineering Data quality assessment and improvement Proficiency in data exploration tools (Pandas, Numpy, Polars) Strong programming skills in Python; R is a plus Deep understanding of: Statistics and probability ML/DL algorithms AI governance and responsible AI practices Experience with: Large-scale data processing Model deployment and MLOps Cost optimization for AI systems Track record of 3-5 successful AI/ML projects in production Excellent communication skills and team leadership ability Continuous learning mindset for emerging AI technologies Skills: Statistics and Mathematics Classical Machine Learning Deep Learning and Neural Networks Generative AI and LLMs Agentic AI Development MLOps and Production Engineering Data Engineering Model Optimization and Tuning AI Governance and Ethics Team Leadership Why join us? Impactful Work: Drive innovation in AI technologies while safeguarding Tanla's assets, data, and reputation Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with clear paths for professional advancement Innovative Environment: Work with a world-class team on cutting-edge AI technologies in a challenging and collaborative environment Research Opportunities: Contribute to the advancement of GenAI and Agentic AI technologies Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com