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

Overview

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 ₹2,000,000.00 per year

Benefits:

• Provident Fund

Experience:

• python: 2 years (Preferred)
• Data science: 4 years (Preferred)

Work Location: Remote