Data Analytics - Senior Professional

* Overview

An accomplished Expert Data Scientist with 10+ years of experience, specializing in classical machine learning, statistical modeling, and end-to-end ML lifecycle management.

Demonstrated ability to take complete ownership of AI/ML initiatives, mentor teams, and collaborate closely with architects and product managers to drive accountable, high-impact solutions.

Exposure to GenAI and agentic AI systems is an added advantage.

Key Responsibilities


* Machine Learning & Statistical Modelling (Core Focus)



* Design, build, and optimize robust ML models across regression, classification, clustering, and time series forecasting problems.



* Lead advanced feature engineering, data quality assessments, and exploratory data analysis.



* Apply strong statistical methods, experimental design (DOE), and rigorous performance evaluation techniques.



* Develop scalable, production-grade ML pipelines with a focus on reliability, maintainability, and performance.

Ownership, Mentorship & Cross-Functional Leadership


* Take end-to-end ownership of ML solutions-from problem definition to deployment and monitoring.



* Mentor junior and mid-level data scientists, fostering best practices in modeling, coding, and experimentation.



* Work closely with architects and product managers to define solution design, align with business goals, and ensure delivery accountability.



* Drive technical direction and contribute to strategic AI/ML roadmap decisions.



* As main DS point-of-contact for a set of use-cases, contribute to the quarterly planning with load estimation of the Data Science activities



* Escalate risk to the AI solution leadership when needed

Cloud ML-Ops & Quality


* Implement robust ML-Ops practices including model versioning, monitoring, and handling data/concept drift



* Ensure high standards of quality through documentation, code reviews, and version control (Git-based workflows).



* Work across cloud ecosystems such as AWS, Azure, or Databricks with flexibility to adapt.

GenAI & Agentic AI (Good to Have)


* Exposure to building LLM-based applications and RAG pipelines using vector databases (FAISS, AI Search, OpenSearch, PGVector, etc.).



* Familiarity with agentic system patterns such as tool usage, multi-agent workflows, and planner-executor architectures.



* Understanding of integration patterns with enterprise systems via APIs and MCP-based tooling.

Innovation


* Stay current on advances in classical ML methods and tools, and the broader AI landscape, and apply them to high-value enterprise use cases.



* Contribute to anticipation/upstream projects as well with technological & scientific watch, IP valorization (patents, publication)



* Promote a culture of experimentation, innovation, and responsible AI, with a focus on fairness, ethics, and trust.

Required Skills & Experience


* 10+ years of experience with stron...