Description

You will build and deploy predictive, prescriptive, and descriptive models that drive measurable business impact.

This role is hybrid.

Responsibilities

• Build and deploy models across classification, regression, time series, clustering, text analytics, or reinforcement learning.
• Execute the full modeling lifecycle, including data mining, wrangling, and transformation of structured and unstructured data.
• Apply advanced techniques such as dimension reduction, NLP, sentiment analysis, anomaly detection, and geospatial analytics.
• Perform qualitative and quantitative analysis, interpreting and extrapolating data for statistical research.
• Manage data validation, cleansing, and information analysis to ensure data integrity.

Required Skills

• 5+ years of experience in data science and statistical modeling.
• Advanced proficiency in Python and R.
• Expertise in SQL and complex querying to pull and transform your own data.
• Experience with Apache Spark, Azure Data Factory, Azure DevOps, Hadoop, Microsoft Azure, Databricks, or AWS.
• Deep understanding of data models, large datasets, and the modeling lifecycle.
• Strong knowledge of data engineering concepts, ETL tools, and data integration.
• Familiarity with data governance, data warehousing, and data mapping.
• Doctoral degree in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.

Preferred Skills

• Familiarity with Agile frameworks (SAFe) and project management delivery excellence.

Key Skills

Education

Any Graduate