Job Description

Role Purpose

The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters

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Required Skills: 

Core Data Science & Analytics

· Demonstrate strong expertise in data exploration, feature engineering, statistical modeling, and predictive analytics, with the ability to operationalize models in production environments.

· Have deep proficiency in Python (preferred) and/or R, with experience using modern data science libraries such as NumPy, Pandas, Scikit-learn, and PyTorch or TensorFlow.

· Be highly proficient in SQL and experienced in working with large-scale data warehouses and data pipelines.

Machine Learning & AI Engineering

· Possess strong experience developing, evaluating, and deploying machine learning and deep learning models across the model lifecycle.

· Experience building and deploying models using modern ML and MLOps practices, including experiment tracking, model versioning, CI/CD for ML, and monitoring.

· Familiarity with cloud-based ML platforms (AWS preferred) and distributed data processing frameworks (e.g., Spark).

Generative AI & Agentic Systems

· Hands-on experience with Large Language Models (LLMs) and Generative AI frameworks, including prompt engineering, retrieval-augmented generation (RAG), and model orchestration.

· Experience building AI agents or agentic workflows capable of reasoning, tool use, multi-step task execution, and autonomous decision-making.

· Familiarity with LLM application frameworks (e.g., LangChain, LlamaIndex, or similar orchestration frameworks).

· Experience with vector databases, embeddings, and semantic search for building knowledge-driven AI systems.

Agentic Coding & AI-Assisted Development

· Strong understanding of AI-assisted software development workflows, including agent-based coding, code generation, automated debugging, and evaluation loops.

· Experience integrating LLMs with APIs, internal tools, and data systems to build production-grade AI copilots or autonomous workflows.

Business Impact & Communication

· Ability to translate complex technical concepts into clear business insights, communicating effectively with both technical and non-technical stakeholders.

· Strong analytical thinking with the ability to work with ambiguous or incomplete data, develop creative analytical approaches, and connect results to business outcomes.

Domain & Collaboration

· Experience applying data science in digital marketing, customer analytics, or growth analytics is highly desirable but not mandatory.

· Comfortable collaborating with engineering, product, and business teams to build scalable data products and AI-driven solutions.

Competencies