Job Description • Build and deploy ML models—especially time series forecasting and NLP—using Azure ML, Databricks, Spark, and MLflow. • Work through open ended, ambiguous analytical problems where data quality, structure, or requirements may be unclear or evolving. • Explore, profile, and transform raw, messy datasets into structured, actionable insights. • Structure unstructured and semi structured data, including document parsing, text extraction, and metadata organization. • Design experiments, iterate rapidly, and test hypotheses in situations with partial or changing business requirements. • Communicate complex findings to non technical stakeholders and collaborate with engineers and domain experts. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements • 3+ years of data science experience with strong ML skills in time series and/or NLP. • Hands on experience with Databricks (Spark, MLflow) and the Azure data/ML ecosystem. • Experience with oil & gas data or similar industrial datasets. • Strong Python skills and expertise in data wrangling, EDA, and handling unstructured data (e.g., PDFs, logs, sensor data, documents).