Data / ML Scientist (Clustering, Trends & Root-Cause)

Job Description

Qualifications ● 4 + years in data science or machine-learning roles (NLP or time-series a plus). ● Hands-on with clustering, anomaly detection, and causal-inference techniques. ● Strong Python (pandas, scikit-learn, PyTorch/TensorFlow) and solid SQL. ● Experience turning notebooks into production jobs via Airflow, Flyte, or similar. ● Comfortable with vector databases and similarity search (Faiss, PGVector, etc.). ● You think in experiments, communicate results clearly, and love shipping incrementally. Key Responsibilities ● Pattern Discovery – Build unsupervised / semi-supervised models (HDBSCAN, metric learning, spectral, etc.) that group similar issues and surface them for human review. ● Trend Detection & Forecasting – Design change-point and anomaly detectors, then forecast issue volume with Prophet, NeuralProphet, or your tool of choice. ● Cross-Channel Correlation – Link signals across chat, email, voice, and social to reveal how pain points bounce between channels. ● Root-Cause & Prescriptive Modeling – Apply causal graphs or lightweight GNNs to suggest likely drivers and remediation actions. ● Active-Learning Loops – Create feedback workflows that let analysts merge/split clusters and continuously improve model accuracy. ● Experimentation & Metrics – Define success criteria, run controlled experiments, and publish clear, visual results for the team. ● Collaboration – Partner with the LLM, platform, and dashboard engineers to deliver end-to-end features—then measure the lift. Job Type: Full-time Pay: Up to ₹1,000,000.00 per year Benefits: Provident Fund Schedule: Morning shift Supplemental Pay: Performance bonus Experience: machine learning: 4 years (Preferred) data science: 4 years (Preferred) python: 2 years (Required) Work Location: In person