Data Scientist

Stefanini Group•Dearborn, MI

16h•Onsite

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.