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: Data Scientist

Positions: 1

Experience: 2 to 5 years

Location(s): Mumbai

Type: On-site / Permanent

Salary: Up to INR 20 LPA (Including 5% to 10% variable)

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