Group Technical Architect
India
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Job Description
Group Technical Architect
Bengaluru, Karnataka

Job Summary

Data Scientist / Machine Learning Engineer (Predictive Analytics)Agentic AI

About the Role

We are seeking a versatile Data Scientist / Machine Learning Engineer to drive high-impact predictive analytics solutions. You will focus on diverse operational challenges, ranging from predictive asset maintenance to dynamic workforce optimisation and demand forecasting. You will leverage the Databricks platform on AWS to build, scale, and deploy robust ML models that integrate seamlessly with our clients' enterprise architectures (SAP, FSM, GIS, SCADA systems).

Key Responsibilities

  • End-to-End Predictive Modelling: Design and develop advanced predictive models to solve complex business problems, such as forecasting daily/hourly reactive workloads, predicting asset failures, and optimising resource allocation.
  • Databricks Ecosystem Mastery: Utilise Databricks (Unity Catalog, Delta Lake, MLflow) to ingest, process, and analyse large-scale structured and unstructured data from diverse sources (e.g., SAP Datasphere, S3).
  • Algorithm Versatility: Apply a wide range of ML techniques, including time-series forecasting (e.g., Prophet, XGBoost, LSTMs), statistical modelling, Bayesian Modelling and optimization algorithms (e.g., Operations Research, Linear Programming) based on the specific use case.
  • Scenario Simulation: Build models that allow business users to simulate various operational scenarios (e.g., tweaking risk appetites, reallocating shifts) and evaluate projected outcomes.
  • Cross-Functional Collaboration: Work alongside Data Engineers, Gen AI Experts (AWS Bedrock), and UI Developers to build "Compound AI" systems that combine predictive insights with generative AI explanations and user-friendly interfaces.

Required Skills & Qualifications

  • Experience: Proven track record as a Data Scientist/ML Engineer delivering predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases.
  • Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow).
  • Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem.
  • Mathematical Foundation: Strong understanding of probability, time-series analysis, and constrained optimization problems.
  • Problem Solving: Ability to translate ambiguous business into structured mathematical frameworks.
  • Experience in Energy & Utilities industry is a definite advantage.

Key Responsibilities

Data Scientist / Machine Learning Engineer (Predictive Analytics)Agentic AI

About the Role

We are seeking a versatile Data Scientist / Machine Learning Engineer to drive high-impact predictive analytics solutions. You will focus on diverse operational challenges, ranging from predictive asset maintenance to dynamic workforce optimisation and demand forecasting. You will leverage the Databricks platform on AWS to build, scale, and deploy robust ML models that integrate seamlessly with our clients' enterprise architectures (SAP, FSM, GIS, SCADA systems).

Key Responsibilities

  • End-to-End Predictive Modelling: Design and develop advanced predictive models to solve complex business problems, such as forecasting daily/hourly reactive workloads, predicting asset failures, and optimising resource allocation.
  • Databricks Ecosystem Mastery: Utilise Databricks (Unity Catalog, Delta Lake, MLflow) to ingest, process, and analyse large-scale structured and unstructured data from diverse sources (e.g., SAP Datasphere, S3).
  • Algorithm Versatility: Apply a wide range of ML techniques, including time-series forecasting (e.g., Prophet, XGBoost, LSTMs), statistical modelling, Bayesian Modelling and optimization algorithms (e.g., Operations Research, Linear Programming) based on the specific use case.
  • Scenario Simulation: Build models that allow business users to simulate various operational scenarios (e.g., tweaking risk appetites, reallocating shifts) and evaluate projected outcomes.
  • Cross-Functional Collaboration: Work alongside Data Engineers, Gen AI Experts (AWS Bedrock), and UI Developers to build "Compound AI" systems that combine predictive insights with generative AI explanations and user-friendly interfaces.

Required Skills & Qualifications

  • Experience: Proven track record as a Data Scientist/ML Engineer delivering predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases.
  • Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow).
  • Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem.
  • Mathematical Foundation: Strong understanding of probability, time-series analysis, and constrained optimization problems.
  • Problem Solving: Ability to translate ambiguous business into structured mathematical frameworks.
  • Experience in Energy & Utilities industry is a definite advantage.

Skill Requirements

Data Scientist / Machine Learning Engineer (Predictive Analytics)Agentic AI

About the Role

We are seeking a versatile Data Scientist / Machine Learning Engineer to drive high-impact predictive analytics solutions. You will focus on diverse operational challenges, ranging from predictive asset maintenance to dynamic workforce optimisation and demand forecasting. You will leverage the Databricks platform on AWS to build, scale, and deploy robust ML models that integrate seamlessly with our clients' enterprise architectures (SAP, FSM, GIS, SCADA systems).

Key Responsibilities

  • End-to-End Predictive Modelling: Design and develop advanced predictive models to solve complex business problems, such as forecasting daily/hourly reactive workloads, predicting asset failures, and optimising resource allocation.
  • Databricks Ecosystem Mastery: Utilise Databricks (Unity Catalog, Delta Lake, MLflow) to ingest, process, and analyse large-scale structured and unstructured data from diverse sources (e.g., SAP Datasphere, S3).
  • Algorithm Versatility: Apply a wide range of ML techniques, including time-series forecasting (e.g., Prophet, XGBoost, LSTMs), statistical modelling, Bayesian Modelling and optimization algorithms (e.g., Operations Research, Linear Programming) based on the specific use case.
  • Scenario Simulation: Build models that allow business users to simulate various operational scenarios (e.g., tweaking risk appetites, reallocating shifts) and evaluate projected outcomes.
  • Cross-Functional Collaboration: Work alongside Data Engineers, Gen AI Experts (AWS Bedrock), and UI Developers to build "Compound AI" systems that combine predictive insights with generative AI explanations and user-friendly interfaces.

Required Skills & Qualifications

  • Experience: Proven track record as a Data Scientist/ML Engineer delivering predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases.
  • Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow).
  • Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem.
  • Mathematical Foundation: Strong understanding of probability, time-series analysis, and constrained optimization problems.
  • Problem Solving: Ability to translate ambiguous business into structured mathematical frameworks.
  • Experience in Energy & Utilities industry is a definite advantage.

Other Requirements

Data Scientist / Machine Learning Engineer (Predictive Analytics)Agentic AI

About the Role

We are seeking a versatile Data Scientist / Machine Learning Engineer to drive high-impact predictive analytics solutions. You will focus on diverse operational challenges, ranging from predictive asset maintenance to dynamic workforce optimisation and demand forecasting. You will leverage the Databricks platform on AWS to build, scale, and deploy robust ML models that integrate seamlessly with our clients' enterprise architectures (SAP, FSM, GIS, SCADA systems).

Key Responsibilities

  • End-to-End Predictive Modelling: Design and develop advanced predictive models to solve complex business problems, such as forecasting daily/hourly reactive workloads, predicting asset failures, and optimising resource allocation.
  • Databricks Ecosystem Mastery: Utilise Databricks (Unity Catalog, Delta Lake, MLflow) to ingest, process, and analyse large-scale structured and unstructured data from diverse sources (e.g., SAP Datasphere, S3).
  • Algorithm Versatility: Apply a wide range of ML techniques, including time-series forecasting (e.g., Prophet, XGBoost, LSTMs), statistical modelling, Bayesian Modelling and optimization algorithms (e.g., Operations Research, Linear Programming) based on the specific use case.
  • Scenario Simulation: Build models that allow business users to simulate various operational scenarios (e.g., tweaking risk appetites, reallocating shifts) and evaluate projected outcomes.
  • Cross-Functional Collaboration: Work alongside Data Engineers, Gen AI Experts (AWS Bedrock), and UI Developers to build "Compound AI" systems that combine predictive insights with generative AI explanations and user-friendly interfaces.

Required Skills & Qualifications

  • Experience: Proven track record as a Data Scientist/ML Engineer delivering predictive models into production environments, ideally for operational, supply chain, or critical infrastructure use cases.
  • Programming: Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow).
  • Platform Expertise: Deep, hands-on experience with Databricks and the AWS cloud ecosystem.
  • Mathematical Foundation: Strong understanding of probability, time-series analysis, and constrained optimization problems.
  • Problem Solving: Ability to translate ambiguous business into structured mathematical frameworks.
  • Experience in Energy & Utilities industry is a definite advantage.
Apply now
Information at a Glance

Why HCLTech?

At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first.

HCLTech is a global technology company, home to more than 227,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending December 2026 totaled $14.7 billion.
23 Benefits At HCLTech, we believe in empowering our employees with comprehensive benefits that support their professional growth and enhance their well-being. When you sign up for a career with us, you gain access to: https://rmkcdn.successfactors.com/147eb21f/a701dca9-f32d-4fc9-9447-6.svg Industry-benchmarked compensation https://rmkcdn.successfactors.com/147eb21f/b0c54381-ddcc-4a33-9b35-9.svg Best-in-class healthcare benefits https://rmkcdn.successfactors.com/147eb21f/b73027be-7aae-4d36-a090-4.svg Personal time off https://rmkcdn.successfactors.com/147eb21f/d5b4fdfd-2e99-4e26-9878-9.svg Maternity and paternity benefits https://rmkcdn.successfactors.com/147eb21f/3d42b0fc-4652-435a-9ece-c.svg Access to skills / higher education programs/resources https://rmkcdn.successfactors.com/147eb21f/aeddeaf2-9e25-4584-ad11-d.svg Discounts on products and services via Benefit Box https://rmkcdn.successfactors.com/147eb21f/a9609a3b-2700-4b3c-9d90-a.svg Participate in CSR programs and live life with a purpose https://rmkcdn.successfactors.com/147eb21f/c6e33851-710f-4634-bd69-f.svg Opportunities to grow and advance your career Note: The benefits listed above vary depending on the nature of your employment and the country where you work. Some benefits may be available in some countries but not in all.