Data Scientist - Python + Deterministic Analytics

Role Overview

We are seeking an experienced Data Scientist with strong expertise in Python, Deterministic Analytics, and Databricks to develop scalable analytical solutions that drive business decisions. The ideal candidate will have a strong foundation in statistics, data engineering, and advanced analytics, with experience leveraging cloud-based data platforms to solve complex business challenges.

Key Responsibilities

• Develop and deploy data science and analytics solutions using Python and Databricks.
• Design and implement deterministic and rule-based analytical models for forecasting, optimization, and decision support.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and actionable business insights.
• Build and maintain scalable data pipelines for data ingestion, transformation, and processing.
• Utilize Databricks and Spark-based frameworks for large-scale data processing and analytics.
• Conduct statistical analysis, hypothesis testing, and performance evaluation.
• Collaborate with business stakeholders to translate business requirements into analytical solutions.
• Develop dashboards, visualizations, and reports to effectively communicate findings.
• Ensure data quality, governance, and compliance standards are met.
• Document methodologies, models, and analytical processes.
• Partner with cross-functional teams including Data Engineering, Product, and Business teams.

Required Skills & Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field.
• 4+ years of experience in Data Science, Analytics, or Data Engineering roles.
• Strong programming expertise in Python.
• Hands-on experience with:
  • Pandas
  • NumPy
  • SciPy
  • Scikit-learn
  • Matplotlib / Seaborn
• Experience with Deterministic Analytics, business rules modeling, and decision frameworks.
• Strong understanding of statistics, probability, and hypothesis testing.
• Experience with SQL and large-scale data processing.
• Hands-on experience with Databricks, Apache Spark, and distributed data processing.
• Experience working with cloud platforms such as Azure, AWS, or GCP.
• Knowledge of data modeling, ETL/ELT pipelines, and data governance practices.
• Experience using Git and CI/CD practices.

Preferred Skills

• Experience with predictive analytics and machine learning techniques.
• Knowledge of optimization algorithms and operational analytics.
• Experience with Power BI, Tableau, or other BI visualization tools.
• Familiarity with MLOps and model deployment frameworks.
• Experience working in Agile delivery environments.

Good to Have

• Experience in the Energy, Utilities, Oil & Gas, Renewable Energy, or Power Generation domain.
• Familiarity with energy forecasting, consumption analytics, asset performance monitoring, or grid analytics.
• Certifications in Databricks, Azure Data Science, AWS Analytics, or related technologies.
• Exposure to GenAI/AI-driven analytics solutions.