Job Description: Senior / Lead Data Scientist

Experience: 6–9 Years Location: [Noida]

Department: Data Science & Analytics

About the Role

We are looking for a Senior / Lead Data Scientist with 6–9 years of hands-on experience to drive end-to-end data science initiatives — from problem framing and experimentation to deploying production-grade ML solutions. You will lead a team of data scientists, partner with engineering and product stakeholders, and own the technical roadmap for advanced analytics and machine learning across the organization.

Key Responsibilities

- Lead the design, development, and deployment of machine learning and statistical models to solve high-impact business problems.
- Own the full ML lifecycle: data exploration, feature engineering, model development, validation, deployment, monitoring, and retraining.
- Mentor and guide a team of 3–6 data scientists; conduct code/model reviews and set best practices.
- Collaborate with product managers, data engineers, and business stakeholders to translate ambiguous business problems into well-defined data science solutions.
- Build and productionize ML pipelines in partnership with ML engineering teams (MLOps).
- Drive experimentation frameworks (A/B testing, causal inference) and define success metrics.
- Develop and fine-tune Generative AI / LLM-based solutions (RAG pipelines, prompt engineering, model fine-tuning) where applicable.
- Communicate insights and model outcomes to senior leadership through clear storytelling and visualization.
- Stay current with the latest research and evaluate current tools, techniques, and frameworks for adoption.
- Ensure model governance: fairness, explainability, reproducibility, and compliance.

Required Technical Skills

Programming & Tools





- Expert-level Python (NumPy, Pandas, Scikit-learn, statsmodels); working knowledge of R is a plus
- Strong SQL (complex queries, window functions, query optimization)
- Version control with Git/GitHub/GitLab; comfort with CI/CD workflows

Machine Learning & Statistics

- Supervised/unsupervised learning: regression, classification, clustering, ensemble methods (XGBoost, LightGBM, CatBoost, Random Forests)
- Strong foundation in statistics: hypothesis testing, Bayesian methods, time-series forecasting (ARIMA, Prophet), causal inference, A/B experimentation
- Model evaluation, hyperparameter tuning (Optuna, GridSearch), and handling imbalanced data

Deep Learning & NLP

- Hands-on with TensorFlow / PyTorch / Keras
- NLP: transformers, Hugging Face, embeddings, text classification, NER
- Computer vision experience (CNNs, object detection) is a plus

Generative AI / LLMs

- Experience with LLMs (GPT, Claude, Llama, Gemini), prompt engineering, and fine-tuning (LoRA/PEFT)
- Building RAG pipelines with vector databases (Pinecone, FAISS, Weaviate, ChromaDB)
- Frameworks: LangChain, LlamaIndex

Big Data & Data Engineering

- Distributed computing: Apache Spark / PySpark, Databricks
- Data warehouses: Snowflake, BigQuery, Redshift
- Workflow orchestration: Airflow, Prefect, dbt
- Streaming (Kafka) exposure is a plus

MLOps & Deployment

- Model deployment: Docker,



Kubernetes, FastAPI/Flask, REST APIs
- ML platforms: MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML
- Model monitoring, drift detection, and retraining pipelines

Cloud Platforms

- Strong experience with at least one: AWS / GCP / Azure (compute, storage, ML services)

Visualization & BI

- Tableau / Power BI / Looker, Plotly, Matplotlib, Seaborn
- Dashboarding and executive-level storytelling

Required Qualifications

- Bachelor's/Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field (PhD a plus)
- 6–9 years of industry experience in data science, with at least 2 years in a senior or lead capacity
- Proven track record of deploying ML models to production with measurable business impact
- Experience mentoring junior data scientists and leading cross-functional projects

Preferred / Nice-to-Have

- Publications, patents, Kaggle achievements, or open-source contributions
- Domain experience in [e-commerce / fintech / healthcare / SaaS — customize]
- Experience with recommendation systems, fraud detection, or demand forecasting
- Familiarity with data privacy regulations (GDPR, etc.) and responsible AI practices

Soft Skills

- Strong stakeholder management and executive communication
- Ability to translate business problems into analytical solutions
- Structured problem-solving, ownership mindset, and bias for action
- Team leadership, mentoring, and conflict resolution

What We Offer

- Competitive salary + performance bonus + ESOPs (customize)
- Flexible/hybrid working model
- Learning & development budget, conference sponsorships
- Health insurance and wellness benefits

📌 Senior / Lead Data Scientist (Noida)
🏢 INTERRA INFORMATION TECHNOLOGIES INDIA PRIVATE
📍 Noida