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Contractual Computer Science Statistics Jobs in Massachusetts

Data Science Engineer

Boston, MA · On-site

$124K - $149K/yr

Required : • Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related field. • Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5 ...

Bachelor's degree in computer science, data science, statistics, applied mathematics or related field Years of Experience * 5 years of relevant experience in applying data science techniques to ...

Data Scientist

Boston, MA · On-site

$80 - $130/hr

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 ...

Senior Data Science Engineer

Boston, MA · On-site

$115K - $156K/yr

Bachelor's degree or advanced degree in Data Science, Computer Science, Statistics, or related discipline * Proven experience applying machine learning and statistical modeling to solve real-world ...

Showing results 41-60

Contractual Computer Science Statistics information

What is the difference between Contractual Computer Science Statistics vs Data Analyst?

AspectContractual Computer Science StatisticsData Analyst
Required CredentialsBachelor's or higher in Computer Science, Statistics, or related fields; certifications like SAS, R, or PythonBachelor's in Statistics, Data Science, or related fields; certifications like Excel, SQL, or Tableau
Work EnvironmentProject-based, often contract roles in tech, finance, or research sectorsOffice or remote, analyzing data to inform business decisions across industries
Employer & Industry UsageTech companies, research institutions, consulting firmsBusiness, healthcare, marketing, finance

Contractual Computer Science Statistics professionals focus on applying statistical methods within computer science projects, often on a contractual basis, while Data Analysts interpret data to support business strategies. Both roles require similar technical skills but differ in scope and industry application.

What job categories do people searching Contractual Computer Science Statistics jobs in Massachusetts look for?

The top searched job categories for Contractual Computer Science Statistics jobs in Massachusetts are:

What cities in Massachusetts are hiring for Contractual Computer Science Statistics jobs?

Cities in Massachusetts with the most Contractual Computer Science Statistics job openings:

Infographic showing various Contractual Computer Science Statistics job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, 2% Contract, and 1% Nights. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution.

Principal Data Scientist (AI-assisted Clinical Development) (Boston)

F. Hoffmann-La Roche AG

Boston, MA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Opportunity

A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That’s what makes us Roche. This role is based in the Innovation Accelerator (IA) team, the innovation engine and connective tissue for Design, Data and Data Science innovation strategy within Product Development Data Sciences (PDD). We translate our long‑term PDD vision into actionable strategy, shaping and prioritizing innovative cross‑functional use cases that span PDD, PD, and Pharma. As both integrators and incubators, we explore, prototype, and help productize solutions to deliver impact in close partnership with internal Roche teams and external collaborators. With a mindset rooted in openness, value creation, and adaptability, we navigate the innovation ecosystem to drive transformative impact and future readiness across the organization.

The IA Principal Data Scientist plays a pivotal role in building and deploying AI/ML‑powered digital solutions that transform how we develop medicines. You will partner closely with product managers, software engineers, and UX researchers to design, test, and scale statistical capabilities that unlock actionable insights from clinical, operational, and real‑world data. With a strong product‑thinking mindset and deep technical fluency, you will help create intelligent tools that are scalable, ethical, and built for impact in regulated healthcare environments.

Responsibilities
  • Support or lead the development and application of advanced statistical and machine learning methods for integration into tools and software products in clinical development and decision‑making support.
  • Design and productize the execution of simulation studies to evaluate innovative trial designs and statistical frameworks.
  • Translate complex scientific and operational considerations into software requirements that productize model development and usage, collaborating with domain experts to validate assumptions and interpret results.
  • Independently drive exploratory analysis of complex clinical, biomarker, and operational data to extract insights and develop predictive models.
  • Develop scalable, reproducible pipelines for data processing, model training, evaluation, and deployment in regulated environments.
  • Optimize model performance, ensure algorithmic fairness, proactively mitigate bias or drift in deployed systems, and develop evaluation approaches for algorithms including generative AI (GenAI) components.
  • Co‑lead the architectural design of ML and GenAI systems supporting traceability, compliance, and explainability.
  • Partner with software engineering, product, UX, and science teams to integrate models into real‑world user applications.
  • Contribute to scientific leadership by publishing and presenting novel methodologies in high‑impact venues, both internal and external.
  • Serve as a best‑practice resource for statistical modeling strategies, code quality, and responsible AI principles.
  • Lead or co‑lead cross‑functional data science efforts that impact portfolio strategy and delivery.
Qualifications
  • Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field.
  • 6+ years of experience applying advanced statistical and ML techniques in biomedical, clinical, or digital health domains.
  • Proven expertise in model development, simulation studies, and decision‑support frameworks.
  • Strong hands‑on experience with Python or R, and ML libraries such as scikit‑learn, TensorFlow, PyTorch, or similar.
  • Track record of translating complex domain questions into robust statistical models or ML systems.
  • Experience building pipelines for training, evaluating, and deploying ML solutions in production environments.
  • Demonstrated expertise with real‑world data, Bayesian methods, decision theory, high‑dimensional data, or causal inference.
  • Attention to detail and quality work with ability to manage and prioritize multiple projects simultaneously.
  • Excellent collaboration skills, including statistical consulting skills, interpersonal skills to contribute effectively in cross‑functional team settings, ability to influence others without authority.
  • Capacity for independent thinking and ability to make decisions based upon sound principles.
  • Excellent strategic agility with problem‑solving and critical thinking skills.
  • Respect for cultural differences when interacting with colleagues in the global workplace.
  • Excellent verbal and written communication skills, specifically in the areas of presentation and writing, with ability to explain complex technical concepts in clear language.
Preferred Qualifications
  • Experience leading technical design or mentoring junior team members.
  • Experience applying Agile software development practices, ideally for a product embedding statistical algorithms and/or GenAI.
  • Experience prototyping and launching innovative data science or AI products.
  • Experience deploying ML models in compliant, regulated environments.
  • Experience developing evidence synthesis models or methods (e.g., network meta‑analysis) and/or approaches to construct data‑driven priors for drug development.
  • Experience with Bayesian computing or probabilistic programming languages (PPLs), including Stan, PyMC, brms, or others.
  • Experience with AI‑native software engineering practices.
  • Familiarity with data governance, privacy, and regulatory frameworks relevant to ML in pharma.
  • Exposure to multiple stages of the pharma development life‑cycle (e.g., early development, assessment of external molecules for business development, commercialization).
  • Familiarity with cloud‑native ML architectures, ML Ops tools, or real‑world data pipelines.
  • Strong publication record or external visibility in scientific communities.
Location

Boston, MA. Relocation assistance is not available.

Compensation

The expected salary range for this position based on the primary location of Boston, Massachusetts is $169,100 - $314,000 USD annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job‑related factors permitted by law. A discretionary annual bonus may be available based on individual and company performance.

Benefits and EEO Statement

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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