Data Scientist

1. 2POSITION DESCRIPTION

JOB TITLE

Data Scientist

GRADE

M

DEPARTMENT

Data Science and Decision Management

LOCATION

HO

SUB-DEPARTMENT

TYPE OF POSITION

Full-time

REPORTS TO

Senior Data Scientist

REPORTING INTO

NA

1. ROLE PURPOSE & OBJECTIVE

1. The Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and through the use of advanced statistical analysis, data mining, AI/ML and data visualization techniques, to create solutions that enable enhanced business performance

2. Take initiatives and Ideate analytics projects which have scope of incremental revenue / reducing cost / increased operational efficiency

3. Support in creating custom reports and presentations accompanied by strong data visualization and storytelling to take necessary data driven actionable

4. The role requires involvement in problem definition, data cleansing, hypothesis generation and testing, model training and testing and finally deployment and monitoring of predicted outcomes

5. The candidate will need to rapidly understand business problems, internalize and contextualize domain specific information and identify deployable, pragmatic solutions that are relevant and add real business value

6. The candidate will need to be able to effectively communicate the intended processes, provide a clear understanding of what data is required and available

1. SIZE OF THE ROLE

FINANCIAL SIZE

NON-FINANCIAL SIZE

• NA

• 10 - 50 reports / dashboard

• Coordinate with third party service providers

• Manage various bureau relationships for portfolio reviews for collection triggers and customer pricing related initiatives

• Manage accuracy of data loads and visualization of accurate data to all stakeholders

1. KEY DUTIES & RESPONSIBILITIES OF THE ROLE

1. Business/ Financials

• Engage with business stakeholders to understand their business process and translate business problems into analytical structures and solve using statistical /ML techniques

• Take initiatives and Ideate analytics projects which have scope of incremental revenue / reducing cost/ increased operational efficiency

• Identify and implement new business opportunities with a strategic and long-term view

• Support the Bank’s cross-sell programs through analytics and execute campaigns to promote various offers, enable fulfillment and tracking of different metrics

• Responsible for timely deployment, execution and housekeeping of all the cross-sell campaigns. Enhances and maintains the campaign management systems and recommend improvements to offer constructs

• Maintain a high level of engagement with business. Periodically prepare and communicate learning from campaigns, to ensures enhancements in campaigns construct, efficiency, execution procedure etc.

• Engage with business stakeholders to understand their business process and translate business problems into analytical structures using visualization tools

• Maintain a high level of engagement with business. Periodically prepare and communicate learning from business trends, to ensures enhancements in business growth projections and tracking them against actual business

• Analyze & monitor delinquency and provide necessary recommendations to minimize delinquency rates

• Support in developing and deploying machine learning application scorecards in collaboration with business / risk / policy teams of the bank

• Liaise with credit bureaus for performance tracking of the business and benchmark analysis to provide detailed business insights

• Perform portfolio risk analytics to provide delinquency forecasting, vintage analysis to assess sourcing quality, concentration risk analysis for risk appetite models and good -bad analysis basis bureau scrubs

• Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling and simulations

• Execute ad-hoc data mining and exploratory statistics tasks on large data-sets related to the business 'strategies

• Collaborate with senior data scientists to communicate obstacles and findings to relevant stakeholders in an effort to improve decision making and drive business performance.

• Develop and provide a set of regular MIS, KPIs, Key Drivers & portfolio data across all product and segment areas.

• Setup the analytical capability in providing value-added analysis and MIS review for the product and distribution groups.

• Monitor product performance and competitive environment; highlight important trends, gaps & opportunities for the business; cost-effective marketing, repricing or fee opportunities

• Design, develop & distribute operational and qualitative reporting to provide stakeholders with consistent insights into regulatory matters and operational progress

• Produce periodic and ad-hoc senior management and stakeholder reports with appropriate controls over manual, semi-automated and automated reporting functions

1. Customer (Both Internal & External)

• Supporting infrastructure setup for analytics driven initiatives of the Bank.

• Liaison with IT/DW/Operations departments to ensure accuracy of the data and data governance management through customized MIS and quality management for reliable outcomes for consumption

• Work with marketing and business development teams to determine the best way to target potential clients

• Ensure all deliverables are followed through maker and checker process

• Understand individual products requirements along with business heads to design and help in executing campaigns / dashboards based on business requirements

• Help in developing customized customer level collection strategies for increased collection rates

1. Internal Process

• Liaison with IT/DW/Operations departments to ensure accuracy of the data and data governance management through customized MIS and quality management for reliable outcomes for consumption.

• Support in monitoring models and report model performance and validity statistics

• Constantly look for increasing the efficiency of the team and department resulting into reducing TAT of analytics projects, e.g. Process enhancement, automation etc.

1. Innovation & Learning

• Upskill to new age technologies with respect to machine learning and customer segmentation. Enhance on-job self-learning related to analytics techniques/tools

• Ensure timely completion of training / learning programs assigned time to time

• Upskill to new age technologies with respect to customer segmentation and business tracking. Enhance on-job self-learning related to analytics techniques/tools

1. MINIMUM REQUIREMENTS OF KNOWLEDGE & SKILLS

Educational

Qualifications

• MBA or Equivalent degree

• Degree in Computer Science, Software Engineering, Information Systems, Mathematics or other STEM majors

Experience(Years and Core Experience Type)

• Overall experience of 3+ years preferably in the BFSI domain with specific experience in business analysis skills, segmentation, life cycle management, portfolio risk analytics & predictive analytics

• Experience in using Statistical tools SAS, R, Python, etc. and knowledge of SQL / HIVE etc.

• Experience in using analytics techniques such as cluster analysis, segmentation, AI / ML techniques

• Strong knowledge on Dashboard Building

• Experience in using Visualization tools like Tableau / Power BI / Qlik, Matplotlib, Seaborn, plotly

• Strong experience with common machine learning and deep learning programming languages and libraries (e.g. Python, R, scikit-learn, TensorFlow, Pandas, Numpy, XGBoost, PyTorch and etc.)

• Experience with cleaning, transforming and visualizing large data sets in various data formats (e.g. unstructured logs, XML, JSON, flat files, Avro, Parquet)

• Knowledge of Big Data ecosystem tools (e.g. Hadoop, Hive, Spark, Kafka)

• Solid SQL skills for querying relational databases (e.g., SQL Server, DB2, MySQL, Oracle)

Certifications

• Experience with analytics programming languages (Python and R)

• Experience with visualization tools such as Tableau

• Experience with Agile software development

Functional Skills

• Good in MS office and data Analysis / building reports

• Knowledge of CRM application, Finacle and other banking applications

• Eye for details and reading numbers

• Dashboard Building & Visualization Techniques

• High business acumen with good understanding of banking operations across all channels

• Working experience in complex risk analytics projects covering full credit life cycle is preferred

• Specialism in one or more of the following: reinforcement learning, deep learning, natural language processing, agent-based modelling, image recognition

• Solid interpersonal and communication skills with ability to build strategic relationships and influence stakeholders and deliver presentations to executive audience

Behavioral Skills

• Team work

• Decision making

• Assertiveness

• Structured thinker, effective communicator with excellent written communication skills

• Ability to understand organizational dynamics

• Ability to work with a cross functional team

• Excellent people management & stakeholder management skills

• Good analytical & presentation skills

• Proficiency in English written and verbal communication skills

• Structured thinker, effective communicator with excellent written communication skills

Competencies

• Cross functional engagement

• Vendor management

• Problem solving

• Prior people management experience, with tried and true approaches for mentoring junior staff

• Understanding of the financial sector, to recognise and drive forward opportunities where data science can transform the bank

• Skilled at influencing and communicating to various stakeholders up to executive level

1. KEY INTERACTIONS

INTERNAL

EXTERNAL

• All Functional Heads (Business & Support functions) & their teams

• Data Science & Decision Management team members

• Third Party Service Providers

• Credit Bureaus

PREPARED BY: Ravichandra Cherukuvada

DATE: 12-02-2024

REVIEWED BY : Nitin Kumar

DATE: 20-03-2026

LAST UPDATED BY: TM Team

DATE: 23-03-2026