Data Scientist (AI/ML)

Location: Cambridge, Massachusetts, United States; may telecommute.

Annual salary: $114,088–$133,117 USD, plus potential bonus, stock, and benefits.

Company

hirify.global is a biotechnology company researching, manufacturing, and delivering medicines for serious illnesses across oncology, inflammation, general medicine, and rare disease.

What you will do

• Apply statistical trending, multivariate analysis, and engineering principles to product and method data.
• Develop visualizations to assess and improve analytical method performance using data analytics software.
• Collaborate with analytical scientists, process development scientists, engineers, quality organizations, QC, QA, and manufacturing teams.
• Investigate method issues and support GMP activities, including annual product reviews, regulatory inspections, and process documentation.
• Evaluate new technologies and statistical approaches for process and operational improvements.
• Apply machine learning methods to analyze datasets, including predictive analytics and protein-structure modeling.

Requirements

• Master’s degree or foreign equivalent in Data Science, Computer Engineering, or a related field.
• University-level coursework, research, internship, thesis, or one year of experience in the relevant areas.
• Experience with data analysis and visualization using Power BI and Tableau.
• Experience developing ETL data pipelines with Databricks, Snowflake, and Amazon Redshift.
• Knowledge of time-series analysis, statistical analysis, hypothesis testing, Python, and R.
• Knowledge of AI/ML methods including classification, regression, anomaly detection, deep learning, NLP, predictive analytics, and convolutional neural networks.

Culture & Benefits

• Collaborative, innovative, and science-based work environment.
• Comprehensive medical, dental, vision, life, disability, and flexible spending benefits.
• Retirement and savings plan with company contributions.
• Stock-based long-term incentives and discretionary annual bonus eligibility.
• Paid time-off plans and career development opportunities.
• Flexible work models, including remote and hybrid arrangements where possible.