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Remote Data Science Jobs in Hamden, CT (NOW HIRING)

Relativity

Senior Applied Scientist

Bridgeport, CT · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team operates at the core of Relativity's AI development.

Eleos Law LLP

Epidemiologist

New Haven, CT · On-site +1

$80K - $120K/yr

... data science, and scientific research. Our mission is to apply rigorous scientific methods to ... Hybrid to our New Haven, CT office, or fully remote with approximately 25% travel to the office ...

Relativity

Principal Applied Scientist

Bridgeport, CT · On-site +1

Posting Type Remote/Hybrid Job Overview WHO WE ARE Relativity is a leading legal data intelligence ... Applied Science Team The Applied Science team sits at the core of Relativity's AI development. We ...

pitneybowes

RevOps Analytics Manager

Shelton, CT · On-site +1

$100K - $120K/yr

... Data Science, Applied Math) or equivalent experience. * 4-5 years of experience in data analysis ... Can be either fully remote (anywhere in U.S.) or hybrid model, depending on proximity to Shelton ...

Arvinas

DMPK Scientist

New Haven, CT · On-site +1

... New Haven, CT or a remote role based within the U.S. Principal Responsibilities Key ... In-depth knowledge or expertise on one or several aspects of DMPK science in drug discovery and/or ...

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Remote Data Science information

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.
More about Remote Data Science jobs
What are the most commonly searched types of Data Science jobs in Hamden, CT? The most popular types of Data Science jobs in Hamden, CT are:
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What job categories do people searching Remote Data Science jobs in Hamden, CT look for? The top searched job categories for Remote Data Science jobs in Hamden, CT are:
What cities near Hamden, CT are hiring for Remote Data Science jobs? Cities near Hamden, CT with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Hamden, CT as of June 2026, with employment types broken down into 2% As Needed, 77% Full Time, 19% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.
Data Scientist Manager - Remote

Data Scientist Manager - Remote

Penfield Search Partners

Fairfield, CT • On-site, Remote

Other

Posted yesterday

Job description

Job Description Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com No 3rd party candidates Position Summary We are seeking a strategic and analytically driven professional to support Medical Affairs through advanced analytics, insight generation, and data-informed decision making. This individual will play a key role in transforming complex data into actionable business insights that support launch readiness, engagement strategy, and overall Medical Affairs effectiveness. The ideal candidate combines strong analytical and technical expertise with the ability to communicate findings in a compelling and impactful way to cross-functional stakeholders

Key Responsibilities Insights Analysis Analyze insights collected across Medical Affairs data sources to identify trends, patterns, and stakeholder sentiment. Synthesize findings into actionable recommendations that support strategic decision-making across cross-functional teams. Deliver clear and concise reporting to support business objectives and organizational priorities.

Strategic Storytelling & Communication Present insights, business impact, and strategic recommendations in a compelling, story-driven format to key stakeholders and leadership teams. Translate complex analytical findings into meaningful business narratives that influence decision-making. Data-Informed Strategy & Analytics Support Medical Affairs teams with data, tools, and analytical models that inform prioritization, planning, and engagement strategy.

Conduct ad hoc analyses to support launch preparation, strategic planning, channel engagement optimization, and Medical Expert (ME) identification and segmentation. Contribute to initiatives that enable successful product launches and ongoing business performance optimization. Metrics & Impact Tracking Track, measure, and report Medical Affairs metrics and performance against established targets.

Develop and define innovative approaches for measuring impact and business value. Identify trends and performance gaps requiring strategic course correction or optimization. Cross-Functional Collaboration Partner closely with Medical Affairs stakeholders to understand business needs and develop analytical capabilities that support organizational goals.

Collaborate with IT and other cross-functional teams on infrastructure, systems, tools, models, and reporting capabilities. Requirements Gathering & Process Support Work closely with IT teams to translate business requirements into clear, concise user stories and technical requirements. Support the development and enhancement of scalable analytics solutions and processes.

Dashboard Development & Reporting Partner with IT and technical teams to develop automated, real-time dashboards integrating multiple data sources to support insight generation and impact assessment. Ensure reporting tools provide meaningful, user-friendly visibility into Medical Affairs performance metrics. Therapeutic Area & Market Knowledge Develop and maintain expertise in relevant therapeutic areas, including respiratory disease states, as well as knowledge of Insmed and competitor products to support accurate interpretation of data and market insights.

Launch Planning Support Provide analytics, insights, and strategic support related to product launch planning and execution. Qualifications Bachelor's or Master's degree in Data Science, Analytics, Business Analytics, Statistics, Computer Science, or a related quantitative field required. Advanced degree preferred (MBA, MS, PhD), or Life Sciences qualification (e.g., PharmD) combined with strong analytics and data experience

Experience supporting Medical Affairs analytics, insights generation, and launch-related initiatives within the pharmaceutical or biotechnology industry preferred. Strong experience with SQL, Qlik, Snowflake, Python, and advanced Excel required. Experience developing dashboards, reporting solutions, and analytical models using multiple data sources.

Strong business acumen with the ability to communicate analytical findings to both technical and non-technical audiences. Proven ability to work collaboratively across cross-functional teams in a fast-paced environment. Excellent presentation, communication, and storytelling skills with the ability to influence stakeholders and drive strategic discussions.

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