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machine learning engineer

Piramal Finance

<div>
 
 We are seeking a dynamic Data Scientist to spearhead our BIU team in Mumbai/Bangalore. In this role, you will be focusing on Portfolio and Business Analytics to drive growth and profitability objectives. Your expertise in data analysis, machine learning, and strategic thinking will help support data-driven decision-making within our business.
 
 
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 <ul>
 <li>
 Master's degree in Economics, Statistics, Computer Sciences, Mathematics, Operational Research, CA, or Engineering from a reputed college.
 </li>
 <li>
 This role requires 2+ years of experience in analytics, preferably financial services, retail business
 </li>
 <li>
 Proven track record of leading and mentoring data scientists.
 </li>
 <li>
 Strong proficiency in Python, model development, validation, machine learning, NLP, and marketing analytics.
 </li>
 <li>
 Hands-on experience with analytics tools like R, SQL, Power BI, and MS Excel.
 </li>
 <li>
 Deep knowledge of predictive analytics techniques (machine learning algorithms, logistic &amp; linear regression, decision trees, clustering).
 </li>
 <li>
 Expertise in exploratory data analysis (data preparation, exploration, and visualization).
 </li>
 <li>
 Excellent communication and presentation skills.
 </li>
 </ul>
 
 
 
 
 
 
 Key Roles &amp; Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 
 Data Analysis &amp; Modelling:
 
 .
 </li>
 <li>
 Ensure the accuracy, validity, and robustness of analytical solutions.
 </li>
 <li>
 Stay abreast of the latest advancements in data science and machine learning.
 </li>
 <li>
 
 Business Impact:
 
 </li>
 <li>
 Translate complex data insights into actionable business recommendations.
 </li>
 <li>
 Partner with cross-functional teams to drive data-driven decision-making.
 </li>
 <li>
 Measure and communicate the impact of the team's work.
 </li>
 <li>
 
 Stakeholder Management:
 
 </li>
 <li>
 Build and maintain strong relationships with key stakeholders across the organization.
 </li>
 <li>
 Effectively communicate project progress, findings, and recommendations.
 </li>
 <li>
 Collaborate with senior management to shape the data science roadmap.
 </li>
 </ul>
 
 
 
 
 
 Job Conditions:
 
 
 <ul>
 <li>
 This role requires 2 to 3 years of experience in analytics, preferably financial services,retail
 </li>
 <li>
 Strong expertise in Python, model development, validation, machine learning, NLP, Gen AI and marketing analytics is essential.
 </li>
 <li>
 Exceptional , communication, and project management skills are crucial.
 </li>
 </ul>
 
 
</div>

Data Scientist

HDFC Bank

<div>
 
 
 Vertical : Credit analytics and innovation
 
 
 
 
 Job Purpose
 
 
 
 Looking for exceptional Data Scientist with a proven track record of experience in Predictive analytics.
 
 
 
 
 
 Job Responsibilities(JR) : 6 &ndash; 8 Areas
 
 
 
 
 Actionable (4-6)
 
 
 
 &middot; Scorecard Building and Modelling
 
 
 
 
 &middot; Developing analytical models to assess risk profile of a customer / identifying cross-sell opportunities/fraud control for new and existing customers
 
 
 &middot; Responsible for development and deployment of various scorecards / models for the credit risk / Retail asset products of the Bank within the specified timelines. Ensure the deployment also is line with Bank&rsquo;s strategies so as to gain maximum efficiencies.
 
 
 &middot; Estimate probability of default arising out of the scorecards and monitor deviation from expected default rates.
 
 
 &middot; Monitor portfolio and identify pockets of opportunity for business growth and risk alerts to control NPAs. Communicate these alerts to the respective owners and follow-up for closure
 
 
 
 
 &middot; Formulating data cuts and strategies to assess credit risk for new and existing customers of the Bank. Give feedback to stakeholders to improve the usage of the models
 
 
 
 
 &middot; Develop novel approaches/algorithms in Risk modeling to constantly improve the operational efficacy of current models and its impact to stake holders
 
 
 
 
 &middot; To adopt the latest trends wrt fintech companies by applying the best-in-class financial models, risk strategies
 
 
 &middot; To work on various aspects related to automation of scorecards in Analytics domain.
 
 
 
 
 &middot; Explore data available within the Banks ecosystem but not used currently to meet the above stated business objectives
 
 
 
 
 &middot; Innovation
 
 
 &middot; Thinking, evolving and making significant changes in the processes, techniques, methods so as to save time, energy and money.
 
 
 &middot; Any other assignments depending on the needs of the organization
 
 
 
 
 
 Educational Qualifications
 
 
 
 
 Key Skills
 
 
 
 
 
 1. MCA/MTech/MSc Statistics or Economics/BTech/MBA or equivalent in Computer science/Statistics or related areas with strong inclination towards machine learning algorithms is preferred
 
 
 &middot; Excellent problem solving capabilities with strong fundamentals in computer science
 
 
 &middot; Strong technical &amp; analytical skills
 
 
 &middot; Hands-on experience in data wrangling (ETL), feature engineering, building and deploying scalable machine learning algorithms
 
 
 &middot; Strong written and verbal communication skills
 
 
 &middot; Excellent knowledge of current trends in the field of machine learning/analytics field
 
 
 
 Experience Required
 
 
 <ul>
 <li>
 Experience of 2+ years in analytics/predictive modeling/machine learning
 </li>
 <li>
 Experience of 2+ years in Python/R in building as well as deploying scalable analytics based models
 </li>
 <li>
 Exposure to banking preferable
 </li>
 </ul>
 
 
 
 
 Major Stakeholders
 
 (intra team and cross functional stakeholders, who would need to be interacted with for discharging duties)
 
 
 &middot; Credit Policy
 
 
 &middot; Underwriting
 
 
 &middot; Process
 
 
 &middot; Fraud Control
 
 
 &middot; Product
 
 
 &middot; Credit Bureaus
 
 
 &middot; Third Party Analytics Service Providers
 
 
 &middot; IT
 
 
 &middot; Legal
 
 
 &middot; Information Security
 
 
 
</div>

DBS Bank

<div>
 
 Job Objective
 
 
 
 In order to actively support the Global Financial Markets (GFM) data analytics capability, there is a need of candidate(s) with proper data science experience and skillset to assist in sourcing, compiling, designing, and analyzing GFM&rsquo;s structured and unstructured data into a proper data model framework to facilitate targeting potential business opportunities, process inefficiencies and overall business trends.
 
 
 This Position Will Report To The Head Of Digital And Data, GFM India And Will Be Part Of The Wider DBS Global Financial Markets Data Analytics Team And The Group GFM Data Chapter. The Team Will Set The Data Roadmap Strategy And Execution For The Global Financial Markets Regional Group Across 3 Areas Of Concentration
 
 
 <ul>
 <li>
 Execution &ndash; Data used to enhance the trading execution and strategy evaluations across multi-asset products for in-house and client
 </li>
 <li>
 Optimization &ndash; Portfolio optimization both in-house and client, process optimization with cognitive AI
 </li>
 <li>
 Recommendation &ndash; Data driven insights on business lead opportunities for internal Sales/Trading and external clients
 
 
 </li>
 </ul>
 The role will be centered on delivering data visualization across various BI tools (Tableau, Power BI), Extracting system data, external data sources, loading, cleansing and to delve into analytics and machine learning techniques to extract more meaningful data insights for potential business opportunities.
 
 
 The role will require exposure to and to work with the various BU and SU teams across DBS:
 
 
 <ul>
 <li>
 Treasury Trading teams across all asset-classes (FX, FXO, IRD, EQD, Fixed Income etc.)
 </li>
 <li>
 GFM Retail, Institutional and Wealth Sales teams
 </li>
 <li>
 Business Management functional teams
 </li>
 <li>
 Cross Business Unit exposure to Corp Banking and Wealth Management
 </li>
 <li>
 Data chapter teams across the market and head office
 </li>
 <li>
 Support functions such as IT, Operations, Legal &amp; Compliance, Finance etc.
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Work within the Data Analytics team (across geographies) to partner and represent across GFM teams to assess business needs and identify opportunities to apply data analytics and tools
 </li>
 <li>
 Assist in defining analytical strategy, including analytical approaches, data, and technology requirements
 </li>
 <li>
 Prioritize the book of work in accordance with the revenue impact and achieve the yearly data revenue targets set for the market
 </li>
 <li>
 Streamline data deliverables in co-ordination with multiple business stakeholders across the bank and in alignment with the VUCA business environment
 </li>
 <li>
 Data back-end tasks including, data extraction, transformation and loading as well as using various techniques for data cleansing
 </li>
 <li>
 Explore use cases for GenAI, AI/ML, deep learning / statistical methods to develop advanced data analytics models to uncover irregular and hidden patterns and predict business leads, risk events under comprehensive scenarios, also rolling out existing use cases from region to GFM India
 </li>
 <li>
 Ability to create effective data visualization via BI tools (i.e., Tableau, MS Power BI, Qlik suite) of results to present key findings to senior management and/or other stakeholders with actionable recommendations
 </li>
 <li>
 Collaborating with Business teams for data led experiments / campaigns and measure the outcome and effectiveness
 </li>
 <li>
 Identifying, raising and resolving data gaps, by evaluating business impact and coordinating with Tech team
 </li>
 <li>
 Assist in automating and deploying data analytics models in banking environment
 </li>
 <li>
 Working with lead Data Manager as well as Data Scientist colleagues on building, testing and optimization machine learning models
 </li>
 <li>
 Ideate, explore, assess new data solutions and their business impact, along with procuring budget for the same and taking it till implementation
 </li>
 <li>
 Co-ordinate with data governance teams from India and region, to ensure completion of the governance workflow for data usage and solutions
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 General understanding of Financial Markets, with emphasis on Equity, FX, Credit and Interest Rate cash and derivative products
 </li>
 <li>
 Expert problem-solving skills, strong attention to detail, creative mindset and interest in data analytics
 </li>
 <li>
 Hands-on experience in Python, PySpark and/or R, SQL, or other statistical program languages and/or experience in using commercial statistical analytics tools, e.g., SAS, SPSS Extensive experience in data visualization tools, preferably Tableau
 </li>
 <li>
 Independent self-starter with ability to multitask and efficient project management
 </li>
 <li>
 Effective interpersonal and organizational skills. including stakeholder and leadership management
 </li>
 <li>
 Ability to formulate data solutions in the VUCA business environment, illustrate benefits via POC or MVP prototypes and implement it to drive business benefits
 </li>
 <li>
 Good command of English
 </li>
 <li>
 Have a &lsquo;can-do&rsquo; attitude
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor of Science degree or equivalent in Computer Science or Data Science or equivalent disciplines
 </li>
 <li>
 Degree holders in Math or Statistics with hands-on programming experience, will also be considered
 </li>
 <li>
 Has at least 2-3 years of relevant experience in Data Analysis, Data Science, Business Intelligence or other related fields. Hands-on project experience in developing machine learning models (preferred)
 
 
 </li>
 </ul>
 
 Primary Location
 
 
 
 India-Maharashtra-Mumbai
 
 
 
 Job
 
 
 
 Analytics
 
 
 
 Schedule
 
 
 
 Regular
 
 
 
 Job Type
 
 
 
 Full-time
 
 
 
 Job Posting
 
 
 
 Sep 9, 2025, 2:30:46 PM
</div>

Associate, Data Analyst, Global Financial Market

JPMorganChase

<div>
 
 Job Description
 
 
 
 We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business.
 
 
 As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies.
 
 
 
 Job Responsibilities
 
 
 
 <ul>
 <li>
 Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business.
 </li>
 <li>
 Support development of data science / AIML use cases for the Card business.
 </li>
 <li>
 Help partners in the Card business define their business problems and scope analytical solutions.
 </li>
 <li>
 Build an in-depth understanding of the Card domain and available data assets.
 </li>
 <li>
 Research, design, implement, and evaluate analytical approaches and models.
 </li>
 <li>
 Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets.
 </li>
 <li>
 Communicate findings and obstacles to stakeholders to drive delivery to market.
 
 
 </li>
 </ul>
 
 Required Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in a relevant quantitative field required in an analytical field (e.g., Statistics, Economics, Applied Math, Operations Research, other Data Science fields).
 </li>
 <li>
 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations.
 </li>
 <li>
 Exceptional analytical, quantitative, problem-solving, and communication skills.
 </li>
 <li>
 Excellent leadership, consultative partnering, and collaboration across teams.
 </li>
 <li>
 Knowledge of statistical software packages (e.g., Python) and data querying languages (e.g., SQL).
 </li>
 <li>
 Experience across a broad range of modern analytics tools (e.g., Snowflake, Databricks, SQL, Spark, Python).
 
 
 </li>
 </ul>
 
 Preferred Qualifications, Capabilities, And Skills
 
 
 
 <ul>
 <li>
 Understanding of the key drivers within the credit card P&amp;L is preferred.
 </li>
 <li>
 Financial services background preferred, but not required.
 </li>
 <li>
 Master&rsquo;s degree or equivalent in an analytical field.
 
 
 </li>
 </ul>
 
 ABOUT US
 
 
 
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 About The Team
 
 
 
 Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.
 
 
 The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
</div>

Data Scientist Associate - AI/ML, Python

Cipla

<div>
 
 
 PURPOSE OF THE ROLE
 
 
 
 To lead the development and implementation of data-driven strategies to enhance procurement, planning, third-party manufacturing, and distribution processes. This role aims to leverage advanced analytics and Artificial Intelligence / Machine Learning to optimize operations, drive efficiencies, and support Cipla&rsquo;s commitment to delivering high-quality healthcare solutions.
 
 
 
 
 
 
 KEY RESPONSIBILITIES
 
 
 
 
 
 
 
 Data Strategy Development for Procurement and Planning and Distribution
 
 
 <ul>
 <li>
 Develop and execute a comprehensive Supply Chain data science and AI strategy to optimize supply chain operations that aligns with procurement and planning and distribution objectives, focusing on service levels and cost to serve models
 </li>
 <li>
 Identify and integrate key data sources (internal and external) to enhance visibility and accuracy in procurement decisions and planning &amp; distribution processes.
 </li>
 <li>
 Evaluate and implement emerging technologies and tools (e.g., GenAI, IoT, digital twins) that enhance data collection, analysis, and visualization capabilities.
 </li>
 <li>
 Collaborate with procurement and planning and distribution teams to prioritize data science initiatives that drive operational efficiencies and cost savings.
 </li>
 </ul>
 
 
 
 
 
 Advanced Analytics and Modeling for Supply Chain Optimization
 
 
 <ul>
 <li>
 Lead the initiative to deploy scientific (based on secondary stock and sales data) replenishment strategies in Trade (India and Global markets)
 </li>
 <li>
 Design and implement predictive AI/ML models to enhance demand forecasting accuracy, optimize inventory levels, distribution planning and improve supplier performance evaluation.
 </li>
 <li>
 Drive innovation by exploring and implementing advanced analytics techniques, machine learning models, and AI algorithms to derive insights and create value from large, complex datasets.
 </li>
 <li>
 Utilize machine learning algorithms to analyze historical data and identify trends that inform procurement strategies and planning cycles.
 </li>
 <li>
 Develop advanced analytics solutions to assess the performance of third-party manufacturers and optimize distribution logistics.
 </li>
 </ul>
 
 
 
 
 
 Collaboration and Stakeholder Engagement Across Functions
 
 
 <ul>
 <li>
 Work closely with cross-functional teams, including procurement, supply chain, planning, and IT, to identify data needs and ensure alignment on data initiatives.
 </li>
 <li>
 Support initiatives like Control Towers, Predictive Analytics, and Agentic Process Automation (APA) in alignment with GSCM&rsquo;s roadmap.
 </li>
 <li>
 Facilitate workshops and training sessions to educate stakeholders on data science methodologies and the value of data-driven decision-making in procurement and supply chain operations.
 </li>
 <li>
 Act as a liaison between data science team and business units to ensure that data solutions meet operational requirements and enhance overall performance.
 </li>
 <li>
 Communicate findings, recommendations, and project updates to senior management and key stakeholders as and when required.
 </li>
 </ul>
 
 
 
 
 
 Master Data Governance and Quality Assurance
 
 
 <ul>
 <li>
 Develop and implement master data governance frameworks to ensure data integrity, quality, and security across all data science initiatives related to procurement, planning, and distribution.
 </li>
 <li>
 Design and oversee data quality checks and validation processes to maintain high standards of data accuracy and reliability in analytics outputs.
 </li>
 <li>
 Ensure that all data science and AI initiatives comply with industry regulations, data privacy laws, and internal policies to safeguard sensitive procurement and supply chain information.
 </li>
 <li>
 Develop strategies to protect sensitive data and ensure compliance with data protection regulations, including monitoring and responding to potential data breaches.
 </li>
 <li>
 Ensure robust documentation, model governance, and audit-readiness of all analytics solutions.
 </li>
 </ul>
 
 
 
 
 
 Team Leadership and Development in Data Science
 
 
 <ul>
 <li>
 Lead and mentor a team of data scientists and analysts, machine learning engineers and AI experts fostering a culture of innovation, collaboration, and continuous learning focused on procurement and supply chain challenges.
 </li>
 <li>
 Set clear performance expectations and provide regular feedback to team members to support their professional development in data science applications.
 </li>
 <li>
 Encourage knowledge sharing and best practices within the team to enhance overall capabilities and effectiveness in addressing procurement and supply chain needs.
 </li>
 <li>
 Work closely with the SCM Academy to build data literacy and analytics capability across the function.
 </li>
 </ul>
 
 Represent the function in external forums, awards, and academic collaborations.
 
 
 
 
 
 
 Performance Measurement and Reporting for Continuous Improvement
 
 
 <ul>
 <li>
 Develop key performance indicators (KPIs) to measure the impact of data science initiatives on procurement, planning, third-party manufacturing, and distribution performance.
 </li>
 <li>
 Regularly report on the progress of analytical projects and their outcomes to senior leadership and stakeholders, highlighting successes and areas for improvement.
 </li>
 <li>
 Conduct post-implementation reviews to assess the effectiveness of data-driven solutions and identify opportunities for further optimization in supply chain processes.
 </li>
 </ul>
 
 
 
 
 
 Stake holder Management
 
 
 <ul>
 <li>
 Internal - Global Head of Digital Transformation and Operational Excellence, Procurement Team, Supply Chain Management Team, Planning Team, Finance Team, IT and Data Engineering Teams, Cipla Leadership Group
 </li>
 <li>
 External - Third-party manufacturers and suppliers, Stockists, Logistics service providers, Data analytics vendors and consultants, Regulatory bodies
 </li>
 </ul>
 
 
 
 
 
 ROLE PROFILE REQUIREMENTS
 
 
 
 
 Education
 
 
 
 Master&rsquo;s degree or PhD in Data Science, Statistics, Engineering, Computer Science, or a related field
 
 
 
 Experience
 
 
 
 12-15 years of experience in data science, analytics, or related fields, with a focus on procurement, planning, third-party manufacturing, or distribution and proven experience in leading digital transformation and AI/ML deployment at scale in the pharmaceutical or healthcare industry.
 
 
 
 
 
 
 Functional / Behavioral Skills required to execute the role
 
 
 
 TECHNICAL / FUNCTIONAL COMPETENCIES
 
 
 
 
 <ul>
 <li>
 Proficiency in data science tools, data warehouses and programming languages (e.g., Python, R, SQL, Agentic AI (MCP), AWS, Azure etc.).
 </li>
 <li>
 Experience with machine learning algorithms, statistical modeling, and data visualization tools (e.g., Tableau, Power BI, Gen AI).
 </li>
 </ul>
 
 
 
 
 BEHAVIORAL COMPETENCIES
 
 <ul>
 <li>
 Strong understanding of supply chain processes, procurement strategies, and planning methodologies.
 </li>
 <li>
 Excellent leadership and team management skills.
 </li>
 <li>
 Strong analytical and problem-solving abilities.
 </li>
 <li>
 Effective communication and interpersonal skills, with the ability to influence stakeholders at all levels.
 </li>
 <li>
 Strategic thinking and a results-oriented mindset.
 </li>
 </ul>
 
 
</div>

Lead – Supply Chain Digital transformation & Analytics

Deloitte

<div>
 
 
 Your potential, unleashed.
 
 
 
 
 
 India&rsquo;s impact on the global economy has increased at an exponential rate and Deloitte presents an opportunity to unleash and realize your potential amongst cutting edge leaders, and organizations shaping the future of the region, and indeed, the world beyond.
 
 
 
 
 At Deloitte, your whole self to work, every day. Combine that with our drive to propel with purpose and you have the perfect playground to collaborate, innovate, grow, and make an impact that matters.
 
 
 
 
 
 The team
 
 
 
 
 
 The Information Technology department is responsible for building products and platforms for Deloitte India that focuses on providing extraordinary customer experience by putting design thinking with trailblazing technology in the center of what they do. The diverse team consists of subject matter experts, technology specialists, quality engineers, user experience researchers &amp; designers, data scientists and product managers.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 1.
 
 NLP Model Development
 
 : Design, develop, and implement state-of-the-art NLP algorithms and models to extract insights and patterns from large volumes of textual data. Leverage machine learning and deep learning techniques to tackle NLP tasks such as text classification, entity extraction, and document summarization.
 
 
 
 
 2.
 
 Data Preprocessing and Feature Engineering
 
 : Preprocess and clean textual data to prepare it for analysis and modeling. Perform feature engineering to extract relevant features and representations from raw text, including word embeddings, n-grams, and syntactic features.
 
 
 
 
 
 3.
 
 Model Evaluation and Validation
 
 : Evaluate the performance of NLP models using appropriate metrics and statistical techniques. Conduct rigorous testing and validation to ensure the accuracy, robustness, and generalization of NLP models across different datasets and domains.
 
 
 
 
 
 4.
 
 NLP Integration
 
 : Collaborate with cross-functional teams, including software engineers and product managers, to integrate NLP solutions into production systems and applications. Ensure seamless interoperability and performance optimization of NLP components within larger AI systems.
 
 
 
 
 
 5.
 
 Research and Innovation
 
 : Stay up-to-date with the latest research in NLP and Gen AI, and apply cutting-edge methodologies to real-world problems. Explore new methodologies, tools, and approaches to improve the effectiveness and efficiency of NLP solutions. Contribute to research publications and thought leadership in the field of NLP.
 
 
 
 
 
 6.
 
 Data Analysis and Visualization
 
 : Analyze and interpret results from NLP models to extract meaningful insights and actionable recommendations. Visualize findings using appropriate techniques and tools to communicate complex information effectively to stakeholders.
 
 
 
 
 
 7.
 
 Documentation and Reporting
 
 : Document methodologies, findings, and insights from NLP projects in clear and concise reports. Communicate technical concepts and results to both technical and non-technical audiences, including management and business stakeholders.
 
 
 
 
 
 
 Qualifications:
 
 
 
 
 
 
 
 &bull;Master's or Ph.D. degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
 
 
 
 
 
 &bull;Minimum of 5+ years of proven experience as a Data Scientist with a focus on NLP and 2 years on Gen AI, preferably in industry or research settings.
 
 
 
 
 
 &bull;Strong knowledge of NLP techniques and algorithms, including text preprocessing, feature extraction, and supervised and unsupervised learning methods.
 
 
 
 
 
 &bull;Proficiency in programming languages such as Python or R, and libraries such as NLTK, spaCy, scikit-learn, and TensorFlow/PyTorch for NLP.
 
 
 
 
 
 &bull;Familiarity with data visualization tools such as Matplotlib, Seaborn, or Plotly.
 
 
 
 
 
 &bull;Experience with containerization and orchestration technologies such as Docker and Kubernetes.
 
 
 
 
 
 &bull;Basic understanding of system design and ML-Ops practices.
 
 
 
 
 
 &bull;Excellent problem-solving skills and analytical thinking.
 
 
 
 
 
 &bull;Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
 
 
 
 
 
 &bull;Proven ability to manage multiple projects simultaneously and meet deadlines in a fast-paced environment.
 
 
 
 
 
 
 Preferred Qualifications:
 
 
 
 
 
 
 
 &bull;Experience with deep learning architectures for NLP, such as recurrent neural networks (RNNs), convolutional neural networks (CNNs), and transformer models (e.g., BERT, GPT).
 
 
 
 
 
 &bull;Knowledge of domain-specific NLP tasks and applications, such as chatbots, document understanding, or information extraction.
 
 
 
 
 
 &bull;Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
 
 
 
 
 
 How you&rsquo;ll grow
 
 
 
 
 
 
 
 Connect for impact
 
 
 
 
 
 
 Our exceptional team of professionals across the globe are solving some of the world&rsquo;s most complex business problems, as well as directly supporting our communities, the planet, and each other. Know more in our Global Impact Report and our India Impact Report.
 
 
 
 
 
 
 Empower to lead
 
 
 
 
 
 
 You can be a leader irrespective of your career level. Our colleagues are characterised by their ability to inspire, support, and provide opportunities for people to deliver their best and grow both as professionals and human beings. Know more about Deloitte and our One Young World partnership.
 
 
 
 
 
 
 Inclusion for all
 
 
 
 
 
 
 At Deloitte, people are valued and respected for who they are and are trusted to add value to their clients, teams and communities in a way that reflects their own unique capabilities. Know more about everyday steps that you can take to be more inclusive. At Deloitte, we believe in the unique skills, attitude and potential each and every one of us brings to the table to make an impact that matters.
 
 
 
 
 
 
 Drive your career
 
 
 
 
 
 
 At Deloitte, you are encouraged to take ownership of your career. We recognise there is no one size fits all career path, and global, cross-business mobility and up / re-skilling are all within the range of possibilities to shape a unique and fulfilling career. Know more about Life at Deloitte.
 
 
 
 
 
 Everyone&rsquo;s welcome&hellip; entrust your happiness to us
 
 
 
 
 
 Our workspaces and initiatives are geared towards your 360-degree happiness. This includes specific needs you may have in terms of accessibility, flexibility, safety and security, and caregiving. Here&rsquo;s a glimpse of things that are in store for you.
 
 
 
 
 
 Interview tips
 
 
 
 
 
 We want job seekers exploring opportunities at Deloitte to feel prepared, confident and comfortable. To help you with your interview, we suggest that you do your research, know some background about the organisation and the business area you&rsquo;re applying to. Check out recruiting tips from Deloitte professionals.
 
</div>

<div>
 
 Job Description
 
 
 
 Be a leader committed to understanding customer needs with your advanced knowledge of product development, design, data analytics, and responsible AI delivering impactful, compliant, and scalable solutions.
 
 
 You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high quality products that resonate with clients leveraging AI across machine learning, NLP, retrieval, and generative techniques (with agentic orchestration as one option among many).
 
 
 
 Job Summary
 
 
 
 As a Product Manager in
 
 Legal &amp; Regulatory Control Operations (LRCO) Product
 
 , you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. As a core leader, you act as the voice of the customer and develop profitable products that provide measurable value. You guide successful launches, collect feedback, and ensure top tier client experiences delivering a broad AI toolkit including predictive analytics, machine learning, natural language processing, retrieval‑augmented generation, workflow automation, and agentic approaches as appropriate. With a strong commitment to scalability, resiliency, stability, and responsible AI, you collaborate closely with cross‑functional teams to deliver compliant, high-quality products that exceed customer expectations.
 
 
 
 Job Responsibilities
 
 
 
 <ul>
 <li>
 Own and prioritize the product backlog and roadmap, balancing AI capabilities with core features to meet strategic goals and regulatory constraints.
 </li>
 <li>
 Assist discovery and research to identify AI use cases across ML, NLP, information retrieval (e.g., RAG), optimization, predictive analytics, and workflow automation&mdash;evaluating build/buy/partner options (agentic methods included when they add value).
 </li>
 <li>
 Establish success metrics and instrumentation, including adoption, accuracy/precision/recall, time‑to‑resolution, cost‑to‑serve, reliability/latency, and risk posture.
 </li>
 <li>
 Drive cross‑functional delivery with Engineering, Data Science/ML, UX, Operations, Compliance, Legal, and Risk to ship AI capabilities, classification, anomaly detection, recommendations, and decision support with human‑in‑the‑loop where appropriate.
 </li>
 <li>
 Champion Responsible AI, ensuring data governance, privacy, security, explain ability, fairness, evaluation rigor, monitoring, and model risk management across the model lifecycle.
 </li>
 <li>
 Translate customer pain points into AI powered solutions for example regulatory change intelligence, control monitoring, case triage/routing, knowledge retrieval, evidence synthesis, redaction/PII detection&mdash;and validate via pilots and A/B tests. Support and troubleshooting: partner with teams to resolve issues, prioritize fixes, and drive continuous improvement based on telemetry and customer feedback.
 </li>
 <li>
 Author epics, user stories, and acceptance criteria (including offline/online evaluation plans) and manage delivery using Agile practices and tools (Jira, Confluence).
 </li>
 <li>
 Plan change management for AI features (enablement, documentation, training, support readiness) and track business impact post‑launch.
 </li>
 <li>
 Manage platform and vendor ecosystem (LLM platforms, vector stores, orchestration frameworks, MLOps/monitoring, analytics) to optimize cost, performance, and SLAs.
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 Coach, mentor and motivate project team members, influencing them to act and take accountability for their assigned work
 
 
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 </ul>
 
 Required Qualifications, Capabilities, And Skills
 
 
 
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 Leverage 8+ years of experience or equivalent expertise in product management or a relevant domain.
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 Apply advanced knowledge of the product development lifecycle, design, and data analytics.
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 Lead discovery, ideation, strategy, requirements, and value management in complex environments.
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 Operate effectively in a highly matrixed, complex organization.
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 Translate AI technologies, including machine learning, NLP, and generative AI, into business value.
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 Utilize Agile processes and tools like Confluence, JIRA, and Git.
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 Collaborate with Data Science/ML and Engineering teams; be familiar with AI platforms and tooling.
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 Make data-driven decisions using experimentation, statistical thinking, and telemetry.
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 Apply knowledge of Responsible AI, privacy, security, compliance, and model risk management.
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 Communicate complex AI concepts to non-technical stakeholders and senior leaders effectively.
 </li>
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 Adapt and solve problems with strong organization and execution skills in dynamic environments.
 
 
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 </ul>
 
 ABOUT US
 
 
 
 JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
 
 
 We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
 
 
 
 About The Team
 
 
 
 Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.
 
 
 Operations teams develop and manage innovative, secure service solutions to meet clients&rsquo; needs globally. Developing and using the latest technology, teams work to deliver industry-leading capabilities to our clients and customers, making it easy and convenient to do business with the firm. Teams also drive growth by refining technology-driven customer and client experiences that put users first, providing an unparalleled experience.
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Product Manager

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