Data Scientist

Stefanini GroupDearborn, MI
16hOnsite

About The Position

Stefanini Group is hiring! Stefanini is looking for a Data Scientist, Dearborn, MI (Onsite) For quick apply, please reach out Lokesh Sharma at 248-582-6565/[email protected] We are looking for someone who is responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc.

Requirements

  • ALGORITHMS
  • Python
  • GCP
  • 5+ years experience in relevant field
  • 5+ years of experience in a Data Science role, with a proven track record of delivering models that impact business outcomes.
  • Expert proficiency in Python (specifically libraries like Pandas, NumPy, Scikit-learn, SciPy) or R.
  • Deep understanding of a broad range of ML techniques, including Gradient Boosting (XGBoost/LightGBM), Random Forests, GLMs, and Clustering.
  • Ability to manipulate and extract data from complex, multi-terabyte distributed databases.
  • Mathematics & Statistics: Strong foundation in linear algebra, calculus, and advanced statistical inference.
  • Experience with version control (Git) and writing clean, modular, and maintainable code.
  • Master's Degree

Responsibilities

  • Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making
  • Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making
  • Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends
  • Design, develop, and deploy high-performance machine learning models (supervised, unsupervised, and reinforcement learning) to address business needs such as churn prediction, recommendation engines, or demand forecasting.
  • Lead the design and analysis of large-scale experiments (A/B testing, multivariate testing) to validate hypotheses and measure the impact of product changes.
  • Architect and implement robust data pipelines and feature engineering processes to improve model accuracy and scalability.
  • Evaluate and refine existing algorithms to improve computational efficiency and predictive power.
  • Act as a strategic advisor to leadership, translating complex algorithmic outcomes into business-centric narratives that drive ROI.
  • Mentor junior data scientists and contribute to the team's internal library of best practices, code standards, and research methodologies.
  • Partner with ML Engineers and DevOps to integrate models into production systems, ensuring reliability and monitoring model drift.
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