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Remote Data Science Jobs in Maine (NOW HIRING)

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... Work closely with data scientists, analysts, and other teams to gather requirements, understand ...

$117K - $154K/yr

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... Work closely with data scientists, analysts, and other teams to gather requirements, understand ...

This is a remote/WFH position with all necessary equipment provided. What You'll Do * Lead data ... Bachelor's degree in life sciences, health, clinical, biological, or mathematical field. * No less ...

Senior Healthcare Data Engineer

Portland, ME · On-site +1

$108K - $147K/yr

You can be in-office in either Portland, ME or Manchester, NH or potentially remote You Will ... A bachelor's degree in computer science, mathematics, statistics, economics, engineering, or ...

Location - We are flexible on remote working from home, if you are located in the USA and reside in ... Collaborate with data engineers and data scientists on the central data team to improve the quality ...

A college degree in Computer Science, Data Science, Cybersecurity, or a related domain.  ... remote

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Showing results 1-20

Remote Data Science information

See Maine salary details

$21.9K

$97.5K

$186.1K

How much do remote data science jobs pay per year?

As of Jun 30, 2026, the average yearly pay for remote data science in Maine is $97,503.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,364.00 and $135,239.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

What is the difference between Remote Data Science vs Remote Data Analyst?

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Maine? The most popular types of Data Science jobs in Maine are:
What are popular job titles related to Remote Data Science jobs in Maine? For Remote Data Science jobs in Maine, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Maine look for? The top searched job categories for Remote Data Science jobs in Maine are:
What cities in Maine are hiring for Remote Data Science jobs? Cities in Maine with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Maine as of June 2026, with employment types broken down into 2% As Needed, 70% Full Time, 21% Part Time, and 7% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $97,503 per year, or $46.9 per hour.
Senior Project Manager, Data Science Initiatives

Senior Project Manager, Data Science Initiatives

The Jackson Laboratory

Ellsworth, ME • Remote

$74K - $125K/yr

Other

Posted 4 days ago


The Jackson Laboratory rating

8.3

Company rating: 8.3 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

26th of 103 rated laboratories


Job description

The Senior Project Manager, Data Science Initiatives will play a leadership role within JAX Research, overseeing the planning, facilitating, executing, and delivering high-priority data science projects within established timelines, resource constraints, and defined objectives. This role is an essential point of leadership for the onboarding and setup of new initiatives. This role is responsible for building and standardizing the project management systems, frameworks, and tools that underpin Data Science Initiatives, establishing consistent processes and KPIs that scale across a growing and complex research portfolio. In this research-driven environment, the Senior Project Manager ensures the effective and efficient use of personnel, equipment, funding, and other resources to advance project goals. This role monitors project progress, identifies risks or deviations from expected outcomes, and implements corrective actions as needed. This position operates across cross-functional teams to ensure project objectives are met, stakeholder needs are addressed, and high-quality deliverables are produced. The Senior Project Manager provides clear communication, strategic context, and data-informed recommendations to internal and external stakeholders while driving alignment, accountability, and efficient execution across the project lifecycle.

Remote (with travel to JAX sites as needed) Salary Range: $74,772 - $125,184 based on years of related experience

Key Responsibilities (What you contribute):

  • Build and standardize project management systems, frameworks, tools, and KPIs that reflect best practices and enable consistent, scalable support across complex initiatives.

  • Maintain visibility across the full project portfolio, including intake and setup of new projects, establishing charters, resource plans, and clear frameworks before execution begins.

  • Document and track all active projects at an appropriate level of detail, capturing objectives, milestones, task priorities, team members and roles, commitment levels, decision points, and resource availability (staff, funding, equipment).

  • Partner with leads to map tasks and timelines, identify interdependencies, and ensure alignment across concurrent initiatives.

  • Develop a sufficient understanding of the aims of the sponsors and collaborators to effectively coordinate project teams and serve as a bridge between technical and operational workstreams.

  • Keep projects on track by proactively identifying and resolving blocking issues, unclear priorities, insufficient resources, risks, and deviations from expected outcomes, implementing corrective actions as needed.

  • Coordinate handoffs and ensure continuity as projects transition between phases or team members, including periodic and final review of sponsor satisfaction.

  • Contribute directly to hands-on technical or experimental work, documentation, reports, or publications as project needs require.

  • Mentor and coach a team of project and/or program managers across both technical and emotional intelligence domains.

Knowledge, Skills, and Abilities (What you're good at):

  • Bachelor's degree required/Master's preferred

  • 7 years required/10 years preferred of career project or program manager with experience in driving complex, long-term, strategic projects

  • Proven track record of managing large, complex research programs and cross-functional teams

  • Demonstrated experience being an agent of change with proven track record of influence and driving required operational change.

  • Demonstrated ability to successfully design & implement a project management framework that drives consistency and operational excellence

  • High fluency in risk management, decision making, and problem solving

  • Exceptional communication skills and stakeholder management experience

  • Experience managing budgets and driving measurable business impact

  • Experience building or scaling a project management function within a research organization

  • Familiarity with data science workflows, machine learning project lifecycles, or research operations

  • Experience contributing to documentation and reports

  • Ability to navigate matrixed or cross-functional environments and lead through influence

Why JAX

At JAX, you'll join a missiondriven organization dedicated to advancing human health through cuttingedge science, data innovation, and collaborative discovery. You'll shape partnerships and programs that accelerate breakthroughs in genetics, disease modeling, and translational research.

If you're a strategic thinker, a relationship builder, and a leader who thrives at the intersection of science and technology, we'd love to meet you.

About JAX:

The Jackson Laboratory is an independent, nonprofit biomedical research institution with a National Cancer Institute-designated Cancer Center and nearly 3,000 employees in locations across the United States (Maine, Connecticut, California),Japan andChina. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.

Founded in 1929, JAX applies over nine decades of expertise in genetics to increase understanding of human disease, advancing treatments and cures for cancer, neurological and immune disorders, diabetes, aging and heart disease. It models and interprets genomic complexity, integrates basic research with clinical application, educates current and future scientists, and provides critical data, tools and services to the global biomedical community. For more information, please visitwww.jax.org.

EEO Statement:

The Jackson Laboratory provides equal employment opportunities to all employees and applicants for employment in all job classifications without regard to race, color, religion, age, mental disability, physical disability, medical condition, gender, sexual orientation, genetic information, ancestry, marital status, national origin, veteran status, and other classifications protected by applicable state and local non-discrimination laws.


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