Senior Lead Data Scientist

Incedo

10 - 15 years

15 - 20 Lacs

gurugram

Posted:3 days ago| Platform:

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Skills Required

continuous integration python software development azure data factory artificial intelligence c# natural language processing entity framework anomaly detection sql data bricks linq sql azure cognitive azure search asp.net .net web api mvc ml ocr

Work Mode

Work from Office

Job Type

Full Time

Job Description

Role Description

Define reference architecture (ingestion lakehouse features/vectors models APIs/UX); make build/buy decisions.
Select, train, and operationalize NLP, anomaly/fraud models, and GenAI/RAG components; establish human-in-the-loop.
Implement experiment tracking, model registry, CI/CD for models, automated evaluation, drift monitoring, rollback.
Design retrieval pipelines (chunking, embeddings, vector namespaces), guardrails (prompt policies, allow-lists, PII redaction), and citation-based responses.
Oversee feature store, labelling strategy, and high-quality gold datasets; enforce DQ rules and lineage.
Right-size SKUs; caching/batching; cost/per-token dashboards; SLOs for latency/throughput.
Break down epics/stories, estimate and sequence work, unblock the team, run technical design reviews.
Translate business policy into rule + ML ensembles, present options, risks, and trade-offs.
Establish testing pyramid (unit, data, model evals, e2e), performance targets, observability dashboards.
Produce design docs, runbooks, SOPs; mentor engineers; uplift coding and review standards.

Technical Skills

10+ years of software development experience, with at least 5 years leading AI/ML projects.
Supervised/unsupervised modelling, anomaly detection, NLP (extraction, classification, NER), OCR pipelines; evaluation design (precision/recall, ROC/PR).
LangChain/LangGraph; embeddings; vector databases / Azure Cognitive Search (vector); prompt engineering & safety patterns.
MLflow, model registry, online/offline evals, data/version management; CI/CD for models.
Delta Lake/Lakehouse (bronze/silver/gold), Azure Data Lake Gen2, Databricks/ADF, schema/versioning, Great Expectations/Deequ.
Python (FastAPI), eventing (Event Grid/Service Bus), containerization (AKS/Azure Container Apps), APIM.
Cognitive Search, Azure OpenAI, Key Vault, Monitor/App Insights, Purview, Cosmos DB/Azure SQL.
Technical decision-making, cross-team coordination, stakeholder communication, mentoring.

Nice-to-have skills

Certifications in AI/ML disciplines.
Hands-on experience with explainable AI and AI governance.
Familiarity with regulatory compliance standards for financial data (e.g., SOX, GDPR).

Qualifications

Bachelor's Degree in Computer Science or related science field or equivalent.

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