Associate Data Scientist

Associate Data Scientist Location Atlanta, Georgia; Boston, Massachusetts; Dallas, Texas; New York, New York Position Type Full time At the American Cancer Society, we're working to end cancer as we know it, for everyone. Our employees and 1.3 million volunteers are raising the bar every single day. We are a culture comprised of diverse backgrounds and experience, to better serve our communities. The people who work at the American Cancer Society focus their diverse talents on our lifesaving mission. It is a calling. And the people who answer it are fulfilled. The Associate Data Scientist, IT, Data & Architecture will foundational data science and analytical techniques to drive insights that inform research, business strategy, and organizational decision-making. Working under the guidance of senior data scientists and data engineers, this role contributes to the development of data models, dashboards, and analysis that enhances understanding of program performance, and population health trends. The Associate Data Scientist will work with diverse data sources—including healthcare, demographic, behavioral, and operational datasets—to support projects across research analytics, and business analytics. The ideal candidate is detail-oriented, intellectually curious, and eager to learn modern data tools and methods while growing into an independent, high-impact contributor. This position offers an opportunity to build technical, analytical, and strategic expertise in a collaborative, mission-driven environment that values innovation, scientific rigor, and data ethics.

ESSENTIAL FUNCTIONS

Design, test, and deploy predictive and descriptive models to advance organizational strategy and outcomes, using Python, R, and related frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). 35% Formulate and validate hypotheses through rigorous statistical testing, ensuring models are grounded in scientific and business relevance. 25% advanced statistical, econometric, and machine learning methods to structured and unstructured datasets, including dense domains such as images or genomics. 20% Translate technical results into clear, actionable insights for both technical and non-technical stakeholders through effective storytelling and visualization. 10% Engage cross-functional teams to understand organizational challenges, frame analytical questions, and develop innovative, data-driven solutions that align with business objectives. 10%

EXPERIENCE/QUALIFICATIONS

Minimum Degree Required:

Bachelor's Degree in Computer Science, Engineering, Computational Biology, Econometric or equivalent experience.

Preferred Degree:

Master's Degree Certificate(s) or License(s): N/A Years of experience: 1-3 years of relevant experience. Proven experience as a data scientist from professional experience and/or formal education.

REQUIRED KNOWLEDGE, SKILLS, AND ABILITY

Advanced modeling expertise; Proven experience developing and validating statistical, econometric, and machine learning models for predictive or descriptive applications. Technical proficiency in analytical programming; Expertise in Python (pandas, scikit-learn, NumPy, statsmodels, PyTorch, TensorFlow) or equivalent R packages, strong working knowledge of SQL. Strong quantitative and analytical foundation; Deep understanding of statistical inference, experimental design, and model evaluation metrics. Experience with complex data domains; Skilled in analyzing high-dimensional or unstructured data, such as images, text, or genomics data. Effective communicator and storyteller; Able to translate complex analytical results into clear, actionable insights for diverse audiences. Collaborative and business-focused mindset; Skilled at partnering with cross-functional teams to understand organizational challenges and design data-driven solutions. Entrepreneurial drive and intellectual curiosity; Self-directed problem solver who proactively identifies opportunities for innovation and impact.

PREFERRED KNOWLEDGE, SKILLS, AND ABILITY

Strong proficiency in statistical modeling, machine learning, and predictive analytics using Python (pandas, scikit-learn, TensorFlow, PyTorch) or R, with experience developing and evaluating models on large, complex datasets. Hands-on experience with SQL, data wrangling, and feature engineering, and familiarity with cloud-based data ecosystems such as Azure, Snowflake, or Databricks for scalable data processing. Working knowledge of MLOps practices, including model versioning, experiment tracking (MLflow, DVC), and deployment workflows; experience with Git-based collaboration. Ability to communicate and visualize results effectively using tools such as Power BI, Tableau, matplotlib, or Plotly, translating complex analyses into actionable insights for business and research audiences.

TRAVEL REQUIREMENTS

Occasional travel- 10-15% - may be required for department or program/project meetings, vendor management, or enterprise workshops.

PHYSICAL REQUIREMENTS

Availability and ability to work after hours, weekends, holidays, etc. as needed, to be on call and/or to fulfill job responsibilities and requirements. The starting rate is $85,000 to $95,000. The final candidate's relevant experience/skills will be considered before an offer is extended. Actual starting pay will vary based on non-discriminatory factors including, but not limited to, geographic location, experience, skills, specialty, and education. ACS provides staff a generous paid time off policy; medical, dental, retirement benefits, wellness programs, and professional development programs to enhance staff skills. Further details on our benefits can be found on our careers site at: jobs.cancer.org/benefits. We are a proud equal opportunity employer. Equal Opportunity Employer. See our commitment to a policy of Equal Employment Opportunity to continually ensure equal opportunity to our employees and to our applicants.