Senior Data Scientist - Generative AI

About TechRBM

TechRBM is a fast-growing digital transformation partner to global enterprises, delivering solutions across AI, Cloud, Data Engineering, and Automation. We're scaling from 120+ to 300-500 professionals and are building a high-impact Data Science team to ship measurable business outcomes for clients in BFSI, Retail, Healthcare, Manufacturing, and High-Tech.

Role Overview

We're hiring a Senior Data Scientist who can own end-to-end problem solving-from business discovery and hypothesis design to model deployment and post-production monitoring. You will partner with product, engineering, and client stakeholders to build production-grade ML / AI and GenAI solutions on AWS / Azure / GCP and mentor a small pod (2-5) of data scientists / ML engineers.

Key Responsibilities

• Business & Problem Framing : Engage with client stakeholders to translate objectives into measurable DS / ML use cases, define success metrics (ROI, adoption, accuracy, latency), and create experiment plans.
• Data Strategy & Feature Engineering : Own data acquisition, quality checks, EDA, and feature pipelines across SQL / Spark / Databricks; collaborate with Data Engineering for robust ingestion and transformation (Airflow / dbt).
• Modeling : Build, tune, and compare models for supervised / unsupervised learning, time-series forecasting, NLP / CV, and GenAI (RAG, fine-tuning, prompt-engineering) using Python (pandas, NumPy, scikit-learn, XGBoost / LightGBM), PyTorch / TensorFlow, Hugging Face.
• MLOps & Deployment : Productionize via MLflow / DVC, model registry, CI / CD (GitHub / GitLab), containers (Docker / Kubernetes), and cloud ML platforms (SageMaker / Azure ML / Vertex AI). Expose services via FastAPI / Flask; implement monitoring for drift, data quality, and model performance.
• Experimentation & Causality : Design and analyze A / B tests, apply causal inference techniques (e.g., propensity scoring, DiD) to measure true impact.
• Explainability, Fairness & Compliance : Apply model cards, SHAP / LIME, bias checks, PII handling, anonymization / pseudonymization, and align with applicable data privacy regulations (e.g., GDPR / DPDP).
• Visualization & Storytelling : Build insights dashboards (Tableau / Power BI / Plotly) and communicate recommendations to senior business and technical stakeholders.
• Collaboration & Leadership : Mentor juniors, conduct code and research reviews, contribute to standards, and support solutioning during pre-sales / POCs.

Required Skills & Experience

Education & Certifications

(ref : hirist.tech)

Skills Required

Tableau, Tensorflow, Nlp, Pytorch, Docker, XGBoost, Python, Aws, Power Bi, Sql, Azure ML, Gcp, Spark, Transformers, Databricks, Azure, Kubernetes