Revfin - Data Science Engineer - Machine Learning

As a Data Science Engineer, you will play a critical role in harnessing data to drive smarter decision-making across our EV financing operations. You will collaborate closely with business, product, and technology teams to build and deploy analytical models and scalable data platforms that enhance credit risk assessment, customer segmentation, and portfolio optimization.

Key Responsibilities :

a. Develop and deploy machine learning models to predict credit risk, customer behavior, and loan performance specific to EV financing portfolios.

b. Design and implement end-to-end data pipelines and data processing systems that ingest and transform structured and unstructured data from multiple sources.

c. Work with large datasets to extract insights that support strategic business initiatives, such as dynamic pricing, fraud detection, and portfolio risk management.

d. Collaborate with cross-functional teams including credit, risk, marketing, and IT to translate business problems into data science solutions.

e. Create dashboards and visualizations to communicate complex analytical findings effectively to stakeholders.

f. Continuously monitor and refine deployed models for accuracy, fairness, and regulatory compliance within the NBFC framework.

g. Identify emerging trends and technologies in data science relevant to the EV financing domain to drive innovation.

Required Technical Skills :

a. Strong proficiency in Python (Pandas, NumPy, scikit-learn), and experience with deep learning libraries like TensorFlow or PyTorch.

b. Expertise in distributed data processing frameworks such as Apache Spark and Kafka for streaming.

c. Sound experience in SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra).

d. Hands-on with AWS/Azure/GCP cloud ecosystems including data engineering, analytics, and ML services.

e. Skilled in containerization (Docker) and orchestration (Kubernetes) for deployment at scale.

f. Experience implementing CI/CD pipelines for ML with Jenkins, GitLab, or CircleCI.

g. Competence with data visualization tools like Tableau, Power BI, or custom Python dashboards.

h. Familiarity with credit risk modeling, Basel norms, and NBFC compliance is a strong advantage.

i. Experience with telematics and IoT data integration is preferred.

Education :

- Bachelor's or Master's in Computer Science, Data Science, Machine Learning, Statistics, or related fields.

- Minimum 3-5 years in data science/engineering roles with a focus on financial services or lending analytics.