Data Scientist – AI Platforms

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 – AI Platforms

Positions: 1

Experience: 2 to 5 years

Location(s): Kurla, Mumbai

Type: On-site / Permanent

Salary: Up to INR 22 LPA (Including 10% variable)

JOB DESCRIPTION

Job Title: Data Scientist / Senior Data Scientist – AI Platforms

Department: Data & Analytics (DNA Team)

Reports to: Head – AI Projects

1. Job Purpose Statement

The role is responsible for designing, building, deploying, and maintaining scalable AI-driven and data science solutions that power enterprise platforms. The incumbent will focus on API-based model deployment, platform engineering using modern cloud and DevOps practices, and AI solutions such as Voice Bots, contributing directly to advanced analytics and automation initiatives.

2. Duties & Responsibilities

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Design, develop, and deploy data science and AI models for business use cases.

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Build and maintain production-grade APIs (REST/JSON) for model serving and integration.

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Implement platform engineering solutions using Python, Docker, CI/CD pipelines, and Azure cloud stack.

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Work closely with data, product, and engineering teams to integrate AI solutions.

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Contribute to Voice Bot / Conversational AI solutions including NLP and speech workflows.

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Ensure scalability, security, and reliability of deployed models and APIs.

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Apply MLOps practices such as monitoring, versioning, and automated testing.

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Document technical designs and support ongoing enhancements.

3. Key Challenges

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Deploying and maintaining production-grade AI and ML systems.

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Managing end-to-end model lifecycle in cloud environments.

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Ensuring performance and reliability of APIs at scale.

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Integrating Voice Bots with enterprise platforms and data sources.

4. Decision Making Authority

Decisions made independently:

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Selection of algorithms, frameworks, and development approaches.

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API and deployment pipeline design within approved architecture.

Decisions made in consultation with Manager:

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Overall platform architecture changes.

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Adoption of new tools and prioritization of delivery timelines.

5. Stakeholder Interaction

Internal Stakeholders:

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Head – AI Projects

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Business Analysts

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Engineering and IT Teams

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Information Security Teams

External Stakeholders:

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Technology Vendors

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Implementation Partners

6. Organisational Relationship

Head – AI Projects

↳ Data Scientist / Senior Data Scientist

7. Job Requirements

Professional Qualification:

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Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, or related field.

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3–5 years of experience in Data Science, AI, or ML engineering roles.

Knowledge:

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Python and data science libraries

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API development frameworks (FastAPI/Flask)

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Machine learning algorithms and feature engineering

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Azure cloud and deployment services

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Voice Bot / Conversational AI concepts

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MLOps and DevOps principles

Skills:

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Building and deploying scalable ML APIs

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Containerization using Docker

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CI/CD pipeline implementation

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Cloud-based AI solution deployment

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Strong analytical and communication skills

Competencies:

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Result orientation and execution excellence

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Problem-solving and analytical mindset

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Collaboration and ownership

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Continuous learning and adaptability