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We’re seeking a Data Scientist to help build predictive models, develop advanced analytics solutions, and uncover insights that drive strategic decision‑making. This role partners closely with data engineering, analytics, business leaders, and product stakeholders to solve complex problems using statistical modeling, machine learning, and exploratory analysis.
Job Responsibility:
Build, train, and validate predictive and statistical models using Python, R, or similar tools
Conduct data exploration, feature engineering, and hypothesis testing across large, complex datasets
Develop machine learning pipelines and deploy models into production environments
Partner with cross‑functional teams to translate business needs into analytical solutions
Build dashboards, presentations, and visualizations to communicate insights clearly
Evaluate model performance and monitor metrics to ensure operational accuracy and stability
Work with data engineers on data quality, pipeline optimization, and scalable architectures
Document methodologies, assumptions, and model outputs for technical and non‑technical audiences
Requirements:
3–7+ years of experience in Data Science, Machine Learning, Predictive Analytics, or Applied Statistics
Strong proficiency in Python (Pandas, NumPy, Scikit‑Learn) or R
Experience with SQL and working in cloud data environments (Azure, AWS, or GCP)
Hands‑on experience building predictive models, classification, regression, clustering, or NLP models
Knowledge of statistics, experiment design, and data validation best practices
Ability to explain complex analytical findings to business partners in clear, digestible formats
What we offer:
medical, vision, dental, and life and disability insurance