Data Scientist

Overview

Seeking a Data Scientist to turn complex real-world data into insights and scalable machine learning solutions across the full data lifecycle.

What you'll do

• Collect, clean, and analyze large structured and unstructured datasets from multiple sources.
• Perform exploratory data analysis to understand distributions, relationships, outliers, and missing values.
• Profile and audit datasets for quality, completeness, consistency, and modeling fit.
• Investigate and document data lineage across systems.
• Build and deploy ML models (e.g., regression, classification, clustering, NLP, time-series).
• Design and analyze A/B experiments using causal inference techniques.
• Build dashboards and self-serve analytics tools for stakeholders.

What you'll need

• Experience profiling messy, incomplete, or poorly documented real-world data.
• Proficiency in Python (pandas, NumPy, scikit-learn, and PyTorch or TensorFlow) and/or R.
• Strong SQL skills with hands-on experience in DB2 and SQL Server.
• Experience with Databricks for large-scale processing, feature engineering, and training.
• Familiarity with cloud platforms: Azure or AWS.
• Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow.
• Solid foundation in probability, statistics, linear algebra, and experimental design.

Nice to have

• Experience with deep learning, NLP, computer vision, or Bayesian methods.
• Familiarity with real-time or streaming data pipelines.
• Open-source contributions or published research.