Bengaluru, Karnataka
Job Summary

Role: Senior Data Scientist

To lead advanced data science initiatives, develop predictive models, and drive data-driven decision-making by extracting meaningful insights from complex datasets, enabling business growth and innovation.

Key Responsibilities

Key Responsibilities

Forecasting & Modeling

Design and deploy production-grade forecasting solutions using statistical models (ARIMA, ETS, BSTS) and ML approaches (XGBoost, LightGBM, neural networks)
Engineer sophisticated features : lag features, rolling statistics, external signals, calendar effects, and domain-specific transformations
Implement forecast reconciliation and hierarchical aggregation for complex business structures
Establish rigorous evaluation frameworks : backtesting, time series cross-validation, accuracy metrics, prediction intervals, and drift monitoring

Software Engineering & Infrastructure

Write production-grade Python and R code with modular architecture, comprehensive testing, error handling, and documentation
Build and maintain sophisticated R Shiny applications with integrated JavaScript components
Orchestrate ML pipelines using Kubeflow for automated training, validation, deployment, experiment tracking, and model versioning
Manage infrastructure as code: Databricks workspaces, Azure resources, CI/CD pipelines (GitHub Actions, Azure DevOps), containerization, and secrets management

Analysis, Debugging & Monitoring

Troubleshoot complex issues across the full stack: data pipeline failures, model degradation, API errors, and integration problems
Implement continuous monitoring: automated data quality checks, feature drift detection, performance tracking, and alerting systems
Conduct root cause analysis of forecast errors, identify data anomalies, validate business logic, and communicate findings clearly
Skill Requirements

Required Qualifications

Technical Foundation

Education & Experience :



Master's or PhD with 3+ years delivering end-to-end data science solutions in production
Programming : Strong Python, R and SQL proficiency
Forecasting Expertise : Time series decomposition, seasonality, trend analysis, ensemble methods, probabilistic forecasting, hierarchical reconciliation
Data Engineering : Databricks/Spark/PySpark, Delta Lake, ETL/ELT design, job orchestration, performance tuning
KNIME : Building analytical workflows, data preprocessing, model pipelines, and system integration

End-to-End Capabilities

MLOps: Kubeflow pipeline orchestration, experiment tracking, model registry, automated deployment
Software Engineering: Git workflows, code reviews, testing frameworks (pytest, testthat), modular design, documentation
Application Development: Build RESTful APIs and R Shiny applications from scratch; handle authentication, deployment, and optimization
Cloud Infrastructure: Azure services (Databricks, Blob Storage, Data Factory, Key Vault, Functions), container orchestration, CI/CD

Essential Soft Skills

Autonomy: Self-starter who can take vague requirements and independently drive projects from concept to production
Problem-Solving: Systematic debugging across the full stack—from source data to infrastructure
Business Acumen: Translate business needs into technical solutions; understand when "valuable enough" beats "perfect"
Communication: Present technical work clearly to non-technical audiences; influence decisions with data; write comprehensive documentation
Collaboration: Work effectively with cross-functional teams while maintaining end-to-end ownership
Other Requirements

Preferred (Nice-to-have)

SAP HANA/BW experience, advanced Kubeflow capabilities, Terraform, Kubernetes, PowerBI/Tableau integration, data governance frameworks, multilingual capability
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📌 Senior Data Scientist (India)
🏢 HCLTech
📍 India