Data Scientist ML Engineer: Python, Data bricks & AWS

Sitcon Consulting Services

India

On-site

INR 1,200,000 - 1,800,000

Full time

14 days+
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Job summary

Sitcon Consulting Services is seeking a versatile Data Scientist/ML Engineer to drive predictive analytics using Databricks on AWS. You will build, scale, and deploy ML models for operational challenges such as asset maintenance, workforce optimization, and demand forecasting, integrating with SAP, FSM, GIS, and SCADA systems.

The role requires strong Python skills, hands-on Databricks experience, and the ability to translate business problems into mathematical models, with collaboration across

Qualifications

  • Proven track record delivering predictive models to production for operational, supply chain, or critical infrastructure use cases.
  • Expert-level Python programming (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow).
  • Deep, hands-on experience with Databricks and the AWS cloud ecosystem.
  • Strong understanding of probability, time-series analysis, and constrained optimization.
  • Ability to translate ambiguous business into structured mathematical frameworks.

Responsibilities

  • End-to-End Predictive Modelling: design and deploy models to solve business problems.
  • Databricks Ecosystem Mastery: ingest, process, and analyze data across sources.
  • Algorithm Versatility: apply time-series forecasting and optimization techniques.
  • Scenario Simulation: enable users to test operational scenarios and outcomes.
  • Cross-Functional Collaboration: work with data engineers, Gen AI experts, and UI developers.

Skills

Data Science
Python
Databricks
AWS
Time-series
Forecasting

Tools

Pandas
scikit-learn
PyTorch
TensorFlow

Job description

Data Scientist/ Machine Learning Engineer (Predictive Analytics)

About the Role

We are seeking a versatileData 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 aData 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.

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