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Weekend Data Science Jobs in Cambridge, MA (NOW HIRING)

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

AI Data Science Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their expertise to an innovative ...

Title: Head of Applied AI & Data Science Company: Ipsen Bioscience, Inc. About Ipsen: Ipsen is a mid-sized global biopharmaceutical company with a focus on transformative medicines in three ...

The successful candidate is a seasoned leader with expertise data science and model development and management. This position will be primarily responsible for personal lines product such as ...

Showing results 21-40

Weekend Data Science information

See Cambridge, MA salary details

$41K

$134.2K

$214.8K

How much do weekend data science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for weekend data science in Cambridge, MA is $134,150.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,700.00 and $148,600.00 per year, depending on experience, location, and employer.

What is a weekend data science?

A Weekend Data Science job typically refers to a part-time or contract-based data science position where the primary work hours are on weekends. These roles are ideal for students, professionals seeking extra income, or those looking to gain experience in the data science field without committing to a full-time weekday schedule. Weekend data scientists analyze data, build models, and generate insights just like full-time data scientists but with flexible or reduced hours that fit around a weekend schedule.

What skills and qualifications are needed to thrive as a weekend data scientist?

To thrive as a Weekend Data Scientist, you need strong analytical skills, proficiency in statistics, and expertise in programming languages such as Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools like SQL, machine learning libraries (e.g., scikit-learn, TensorFlow), and data visualization platforms (e.g., Tableau) is typically required. Excellent time management, problem-solving ability, and effective communication are crucial soft skills for delivering insights on tight weekend deadlines. These skills ensure that data-driven decisions can be made efficiently and accurately, even within limited time frames.

What challenges do data scientists working on weekends face, and how can they be managed?

Data scientists working weekend shifts often encounter challenges such as limited access to colleagues for collaboration or support, since many team members may not be available outside standard business hours. Additionally, urgent issues or data anomalies may require quick, independent problem-solving. Proactive communication with weekday teams, thorough documentation, and setting up clear protocols for handoffs can help manage these challenges and ensure smooth workflow continuity.

What is the difference between Weekend Data Science vs Part-Time Data Analyst?

AspectWeekend Data SciencePart-Time Data Analyst
CredentialsTypically requires a degree in data science, statistics, or related fieldOften requires a degree or relevant experience in data analysis or related fields
Work EnvironmentProject-based, flexible hours, often remote or on-site during weekendsFlexible hours, may be remote or on-site, often with less technical complexity
Industry UsageUsed in tech, finance, healthcare, and startups for specialized projectsCommon in retail, marketing, and small businesses for routine data tasks

Weekend Data Science roles focus on complex data projects requiring advanced skills, often during weekends, while Part-Time Data Analysts handle routine data tasks with less technical depth, offering flexible schedules. Both roles serve different needs but share a focus on data work outside standard hours.

Do weekend data scientists work on weekends?

Weekend data scientists may work on weekends depending on project deadlines, company policies, or client needs. Typically, data science roles involve regular weekday hours, but some positions require weekend work, especially in roles with flexible or project-based schedules. It is important to clarify work hours during the hiring process or in job descriptions.

What are the most commonly searched types of Data Science jobs in Cambridge, MA?

The most popular types of Data Science jobs in Cambridge, MA are:

What are popular job titles related to Weekend Data Science jobs in Cambridge, MA?

For Weekend Data Science jobs in Cambridge, MA, the most frequently searched job titles are:

What cities near Cambridge, MA are hiring for Weekend Data Science jobs?

Cities near Cambridge, MA with the most Weekend Data Science job openings:

Head, Innovation Accelerator Data Science

Genentech

Boston, MA

Full-time

Re-posted 20 days ago


Genentech rating

8.8

Company rating: 8.8 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

11th of 86 rated pharmaceutical


Job description

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 Opportunity:

The Head of Innovation Accelerator Data Science is responsible for driving technical excellence across design, data and data science innovation programs for Roche Product Development. This role combines deep subject matter expertise in data science and software development with people leadership and portfolio oversight. The Head of IA Data Science ensures strong technical execution, guides architectural decisions, and aligns technical capacity with strategic goals. As a direct report to the Function Head, this position plays a critical role in shaping the innovation roadmap, scaling capabilities, and growing high-performing technical teams.

  • You provide technical leadership across early exploration and productization phases of innovation projects, ensuring alignment with departmental goals and enterprise direction

  • You act as subject matter expert and single point of escalation/problem resolution for applied data science and software engineering within the innovation portfolio

  • You influence PDD data, design and data science (3D) strategy and in-silico strategy & roadmap(s) through strategic technical leadership/expertise

  • You make architectural decisions independently and ensure adherence to best practices for scalability, performance, reliability, and compliance

  • You oversee execution quality, technical risk management, and project velocity across multiple high-impact workstreams and domains

  • You establish and enforce technical standards, enabling reuse, modularity, and robust design across solution development

  • You lead technical capacity planning and resource deployment within the team, prioritizing based on departmental strategy and portfolio needs

  • You collaborate with cross-functional and enterprise partners to translate innovation opportunities into feasible, impactful, and technically sound solutions

  • You drive the Innovation Accelerator portfolio through contribution to governance, resource planning, and progress reviews

  • You identify and integrate new technologies and platforms, applying functional expertise and organizational context to maximize department performance

  • You ensure traceability, reproducibility, and risk mitigation through robust documentation and engineering practices across all technical deliveries

  • You manage a multidisciplinary team of specialists and junior leaders (e.g., data scientists, software engineers), ensuring accountability for delivery, performance, and development

  • You oversee hiring, onboarding, workforce planning, and succession management aligned to departmental capabilities and strategic growth areas

  • You coach and mentor team members to enhance their individual performance and long-term potential, developing future technical leaders across roles and backgrounds

  • You foster a high-performance, inclusive culture focused on collaboration, ownership, and continuous improvement

  • You set development goals, conduct performance evaluations, and guide career progression based on business priorities and professional aspirations

  • You manage team deployment and resource allocation across a complex portfolio of innovation projects, balancing individual growth with business needs

  • You execute short-term department plans by managing priorities, budget, and capacity in coordination with function leadership

  • You influence senior stakeholders and functional leadership to secure alignment, resources, and sponsorship for technical priorities

Who you are:

  • You have an advanced degree (Master's or PhD) in Computer Science, Data Science, Statistics, Engineering, or a related technical field

  • You have 15+ years of hands-on experience in software engineering, data science, or technical innovation, ideally within R&D or regulated environments

  • You have 4+ years in a leadership role managing multidisciplinary technical teams

  • You have proven experience driving technology delivery from prototyping to scaled implementation

  • You have deep expertise in modern data and software development technologies and architectural practices

  • You are proficient with Python or R, and ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch

  • You have a strong understanding of supervised/unsupervised learning, statistical modeling, and experimental design

  • You are familiar with software development practices including version control, testing, and collaborative coding

  • You have experience running simulations or analyses in a high-performing computing environment

  • You have knowledge of and experience with four or more of the following:

    • Epidemiology, including causal inference methods for observational real world data (RWD) or real world evidence (RWE)

    • Bayesian statistics

    • Decision theory, including multiple criteria decision analysis (MCDA), utility elicitation, decision simulation models, or Value of Information

    • Clinical outcomes research using data from electronic health records (EHR)

    • Discovery mechanisms and evidence generation pathways for novel biomarkers and risk scores

    • Interpretable machine learning

    • Methods to incorporate knowledge graphs, ontologies, or other forms of structured information

    • Probabilistic programming languages

    • Complex or innovative clinical trial designs, including adaptive stopping, seamless Phase 2/Phase 3 designs

  • You have a strong track record in managing resources, planning capacity, and balancing competing priorities

  • You have excellent communication and stakeholder management skills

  • You are fluent in agile delivery, DevOps, or other modern ways of working

  • You have a passion for continuous learning

  • You have a passion for mentoring colleagues of all backgrounds

  • You have capacity for independent thinking and ability to make decisions based upon sound principles

  • You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain

  • You demonstrate respect for cultural differences when interacting with colleagues in the global workplace

  • You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language

Preferred:

  • Experience in pharma, life sciences, or healthtech sectors

  • Familiarity with regulated environments and compliance-driven product development

  • Exposure to innovation frameworks (e.g., lean startup, dual-track agile)

  • Demonstrated ability to assess and integrate emerging technologies (e.g., GenAI, ML Ops, cloud platforms)

Relocation benefits are not available for this posting

The expected salary range for this position based on the primary location of California is $254,400-$472,400. 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. This position also qualifies for the benefits detailed at the link provided below.
Benefits

#PPDT

#PDDSSF

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.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.


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About Genentech

Sourced by ZipRecruiter

A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.

Industry

Scientific research and development services

Company size

10,000+ Employees

Headquarters location

South San Francisco, CA, US

Year founded

1976

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