Data Scientist

• Develop innovative approaches to solve challenging data and analytics problems and uncover actionable insights.
• Identify and prepare relevant data from multiple sources, collaborating with internal subject matter experts as needed.
• Apply advanced statistical analysis, machine learning, and predictive modeling techniques to generate actionable business insights.
• Design experiments, test hypotheses, and construct, validate, and deploy machine learning and AI models.
• Automate, maintain, and improve ML models and pipelines using MLOps best practices.
• Present insights and model results clearly to business stakeholders using dashboards, visualizations, and storytelling.
• Measure outcomes and assess the success of programs and interventions driven by analytics work.
• Stay current with machine learning, deep learning, and AI trends, including LLMs, transformers, and generative AI tools.
• Educate colleagues on new tools, methods, and best practices applicable to data science and analytics.
• Work independently on projects, managing planning, execution, and communication of progress and outcomes.
• Ensure data accuracy, reproducibility, and transparency throughout projects, including proper documentation of workflows and processes.
• Deliver ad-hoc analyses and insights as needed to support business decisions.

• Master's degree in Data Science, Computer Science, Statistics, Mathematics, or equivalent work experience.
• 2+ years of hands-on experience building and deploying machine learning models using a variety of algorithms.
• Proficiency in Python and/or R, with strong programming and scripting skills (SQL, shell scripting). Knowledge of SAS is a plus.
• Solid understanding of statistical analysis, multivariate testing, predictive analytics, forecasting, and optimization techniques.
• Experience with data warehouses, big data platforms, and cloud-based data services (AWS S3, Redshift, Athena, Azure Synapse, BigQuery).
• Familiarity with data architecture, ETL pipelines, and modern data engineering concepts.
• Experience in model deployment and MLOps using tools like MLflow, Kubeflow, AWS SageMaker, or Azure ML.
• Knowledge of data visualization tools (Power BI, Tableau, Matplotlib, Seaborn, Plotly) for communicating insights.
• Familiarity with healthcare systems, insurance claims, or clinical data is a plus but not required.
• Strong problem-solving, critical thinking, and communication skills, with the ability to explain complex models to non-technical stakeholders.
• Commitment to data quality, documentation, and reproducibility throughout the analytics lifecycle
• Location: Candidates must be local to Massachusetts; this position requires some onsite collaboration.

$80-$130/hr, depending on experience and scope.

We are The Hollister Group, the Boston area's leading women-owned staffing firm. We guide candidates through the job search process and connect top-tier talent with opportunities that meet the needs of both our candidates and clients. Our Recruiters will help you refine your goals, improve your resume and interview skills, and stay on the lookout for a position that matches your experience and ambition. Our Technology Staffing Team is looking to speak with Boston-area candidates who would be a strong fit for the role outlined below.