Director Data Science

Location: Vasanthanagar

Leader - Data Science

Incedo Data Modernization Platforms | Data Xel & DQXpert

LOCATION - Gurugram/Bangalore
EXPERIENCE - 14–18 years
REPORTS TO Head of Engineering

ABOUT INCEDO
Incedo is a global AI and data transformation specialist, helping companies turn digital investment into sustainable business impact by  delivering ROI from AI@Scale . We are 4,000+ people across the US, Canada, Latin America and India, working with Fortune 500 enterprises and fast-growing clients in banking & payments, wealth management, telecom, hi-tech and life sciences.
Build what's next in AI, data and enterprise platforms
Our Platform & Solutions portfolio is where Incedo builds AI-native products for real enterprise problems:  Incedo Lighthouse  (AI-powered decision intelligence),  Data Xel  (agentic data modernization),  brAInspark  (agentic AI enablement),  Incedo Pay  (integrated payables),  Kratos  (regulatory compliance and data control for banking) and  DQXpert  (AI-powered data quality) — plus domain products across customer support, document processing, quality engineering, healthcare and financial services.

You'll work with multidisciplinary teams across Product, Engineering, AI/Data, Design and Business, taking ideas from problem discovery and experimentation to production-grade platforms that enterprises depend on.

WHY THIS ROLE
Most Director of Data Science roles sit in one camp: a pure analytics function, or a GenAI product team. This one needs both, working together.
Data Xel needs a data science Leader who can design autonomous agents that take consequential actions on live enterprise data estates — safely. DQXpert needs someone who can make generative AI trustworthy enough that business users will actually act on what it tells them about their data.

THE ROLE
You will be the  Data Science Leader for Data Xel and DQXpert , Incedo’s data modernization product suite. You set the modelling and agentic architecture strategy, lead the data science bench, and own the intelligence layer of both products from prototype to production.
Most Director of Data Science roles sit either inside a pure analytics function or on top of a GenAI product. This one needs both. Data Xel is not a model — it is an autonomous agent taking consequential actions on live enterprise data estates, so it needs someone fluent in multi-step planning, tool orchestration and safe autonomous execution. DQXpert needs generative AI trustworthy enough that business users act on what it tells them — which takes classical ML rigour to build the deterministic guardrails underneath.

WHAT YOU'LL OWN
1. The agentic modernization engine — Data Xel
Lead the design and evolution of Data Xel's agentic architecture: autonomous schema discovery, intelligent mapping, pipeline generation and migration execution, orchestrated across a multi-step agentic loop.
Define the human-in-the-loop gate framework — where approval is required, how confidence and uncertainty are surfaced to the reviewer, and how the system escalates gracefully when thresholds aren't met.
Build the learning system that turns every HITL approval and rejection into a feedback signal that improves future automation.
Partner with data engineering to ensure the agentic execution layer integrates safely with Data Xel's transformation engine.

2. GenAI-powered data quality — DQXpert
Lead the design of DQXpert's GenAI layer: natural-language data profiling, LLM-based anomaly characterisation, and plain-language DQ rule authoring that turns business intent into executable validation logic.
Architect the knowledge context layer behind remediation recommendations — how domain knowledge, past fixes and lineage context get retrieved and injected into prompts to produce specific, trustworthy suggestions instead of generic ones.
Build the continuous improvement loop: track accept/reject behaviour on rules and recommendations, and use it to sharpen what the system surfaces.
Own the classical ML and statistical models where deterministic correctness beats generative fluency — anomaly detection baselines, schema drift scoring, and the DQ metrics the GenAI layer reasons on top of.

3. Platform architecture & MLOps
Define the…