Senior Data Scientist

Hiring for: One of India’s leading non-banking financial companies (NBFCs), focused on driving financial inclusion across rural and semi-urban markets.

Role: Senior Data Scientist

Positions: 1

Experience: 8 to 12 years

Location(s): Kurla, Mumbai

Type: On-site / Permanent

Salary: Up to INR 42 LPA

JOB DESCRIPTION

1. Job Purpose Statement

The Data Scientist will work closely with business stakeholders to understand their challenges, extract and process data and develop Statistical Scorecards, AI/ML models that drive measurable business impact. The role requires strong hands-on expertise in Python, SQL, and Azure ML, and the ability to independently manage end-to-end analytics workflows across lending, collections, risk, customer analytics, and operations.

2. Duties & Responsibilities

·      Manage team of Data Scientists to deliver high impact projects.

·      Ensure end to end project management to deliver on time.

·      Build, validate, and deploy predictive ML models using Python and Azure ML and Databricks.

·      Apply algorithms such as Decision Trees, Random Forest, Gradient Boosting, Logistic Regression, SVMs, and Neural Networks.

·      Create Pipelines & structured codes for processing large scale structured and unstructured data

·      Develop reusable data pipelines for model training, scoring and validation

·      Translate business challenges into clear analytical and ML problem statements

·      Present analytical findings and model results to non-technical stakeholders.

·      Automate model workflows and build scalable scoring pipelines.

·      Generate insights and actionable recommendations from business data.

3. Key Challenges

·      Translating business questions into structured ML problems.

·      Working with complex and incomplete NBFC datasets.

·      Communicating ML concepts in simple terms.

·      Ensuring models are scalable, production-ready, and sustainable.

4. Decision Making Authority

Decisions made independently - Algorithm selection, feature engineering, modelling approach, exploratory data work, and stakeholder communication.

Decisions made in consultation with Manager - Architectural decisions, new tool/platform adoption, and deployment of high-impact models.

5. List of internal and external stakeholders the role is expected to interact with to execute duties effectively

Internal

·      Credit, Risk and Collection Teams

·      Data Engineering Team

·      Data Analytics Team

·      Marketing Team

·      BI & IT Platform Teams

6. Job Requirements

Professional Qualification:

-         Bachelor’s or master’s degree in engineering, Mathematics, Statistics, Computer Science, or related field.

-         8+ years of ML and programming experience.

Knowledge:

-         Python, SQL, Azure ML, ML algorithms, feature engineering, statistical modelling, and experience with end-to-end AI/ML projects, Use of Gen AI tools.

Skills:

-         Strong communication, ability to simplify complex concepts, analytical problem-solving, data integrity, and ability to work in matrix environments.

Competencies:

-         Result Orientation with Execution Excellence

-         Strategic thinking

-         Data storytelling