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Remote Data Science Jobs in Kearny, NJ (NOW HIRING)

Bread Financial

Lead Data Scientist

New York, NY · On-site +1

$144K - $250K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Shaped

Senior Data Scientist

Brooklyn, NY · On-site +1

$100K - $150K/yr

We're remote but have an office in Brooklyn, New York. We're looking for a Senior Data Scientist to help customers integrate and develop recommendation models using the Shaped Platform.

OpenX

Data Scientist III

New York, NY · Remote

Own the end-to-end data science lifecycle for moderately complex models and significant project components -- spanning data ingestion, feature engineering, modeling, validation, deployment ...

OpenX

Data Scientist III

New York, NY · On-site

Own the end-to-end data science lifecycle for moderately complex models and significant project components - spanning data ingestion, feature engineering, modeling, validation, deployment, monitoring ...

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Remote Data Science information

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.

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 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 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.

Can I work remotely as a data scientist?

Yes, many data scientist roles are available as remote positions, especially in companies that prioritize flexible work arrangements. Remote data scientists typically need strong skills in programming, data analysis, and tools like Python or R, and may require familiarity with cloud platforms and collaboration tools. Availability depends on the employer's policies and the specific job requirements.
More about Remote Data Science jobs

What are the most commonly searched types of Data Science jobs in Kearny, NJ?

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For Remote Data Science jobs in Kearny, NJ, the most frequently searched job titles are:

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Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Kearny, NJ as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Actuarial Data Scientist

Berkshire Hathaway GUARD Insurance Companies

Manhattan, NY • On-site, Remote

$120K - $190K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago

Key responsibilities

  • Partner with actuarial teams to develop analytical solutions that improve pricing, risk segmentation, underwriting performance, and profitability.

  • Develop and enhance pricing, segmentation, profitability, and risk selection models using actuarial methodologies and machine learning techniques.

  • Build scalable, production-ready analytical workflows and collaborate with data engineering and technology teams to operationalize models and solutions.

Job description

Overview

Good Things Start Here.

Good things are happening at Berkshire Hathaway GUARD Insurance Companies-an A+ (Superior) rated, nationwide Property & Casualty insurer backed by Berkshire Hathaway. With supportive leadership, collaborative teams, and opportunities to grow, GUARD is a place where people build meaningful, longterm careers.

Good Things You Can Count On.

  • Hybrid schedule: 2 days remote / 3 inoffice
  • Competitive pay + generous PTO
  • Medical, dental & vision starting day one
  • 401(k), tuition reimbursement & longevity bonuses
Responsibilities

We're seeking an Actuarial Data Scientist that would be reporting to the AVP, Data Science & Commercial Lines Pricing. This role combines actuarial analytics, predictive modeling, and technical leadership to advance pricing sophistication, risk segmentation, underwriting performance, and profitability. The successful candidate will help modernize actuarial modeling practices, develop scalable analytical solutions, and promote the adoption of data science and software engineering best practices throughout the organization.

Day-to-day:

  • Partner with actuarial to develop analytical solutions that improve pricing sophistication, risk segmentation, underwriting performance, and profitability.
  • Develop and enhance pricing, segmentation, profitability, and risk selection models across Commercial Lines products using both actuarial methodologies and modern machine learning techniques.
  • Apply advanced analytics to pricing, underwriting, claims, and other insurance datasets to identify trends, emerging risks, and opportunities for profitable growth.
  • Support rate reviews, indication analyses, profitability studies, portfolio management, and other pricing initiatives through advanced analytical techniques.
  • Develop predictive models using GLMs and other statistical and machine learning approaches while balancing predictive performance, business value, interpretability, and regulatory considerations.
  • Research and evaluate internal and external data sources to enhance underwriting, pricing, and portfolio insights.
  • Build scalable, production-ready analytical workflows and collaborate with data engineering and technology teams to operationalize models and analytical solutions.
  • Promote best practices in model development, coding standards, testing, documentation, version control, reproducibility, model governance, and performance monitoring.
  • Provide technical guidance and mentorship to actuarial and analytical teams, helping advance the adoption of modern data science and software development practices.
  • Communicate analytical findings and recommendations to technical and non-technical audiences, including senior leadership, and help drive adoption of analytical solutions across the organization.
Qualifications

Required

  • Bachelor's degree in Actuarial Science, Statistics, Mathematics, Data Science, Computer Science, Engineering, Economics, or a related quantitative field.
  • 3-5 years of experience in Actuarial Data Science field
  • Experience developing predictive models and advanced analytical solutions in a business environment.
  • Strong proficiency in Python, including development of production-quality analytical code.
  • Advanced SQL skills for large-scale data extraction, transformation, and analysis.
  • Experience working with large, complex datasets and statistical modeling techniques.
  • Strong communication, collaboration, problem-solving, and stakeholder management skills.
  • Ability to work independently in a fast-paced environment.

Preferred

  • Experience working with actuarial pricing methodologies.
  • Experience with Commercial Lines products such as Workers Compensation, Commercial Auto, General Liability, Businessowners (BOP), Professional Liability, Umbrella, or similar coverages.
  • Experience leading actuarial or analytical modernization initiatives.
  • Familiarity with Git or Azure DevOps, code review processes, CI/CD concepts, package management, and collaborative development workflows.
  • Familiarity with model governance, validation, and monitoring frameworks.
  • Candidates with combined actuarial and data science backgrounds are strongly encouraged to apply.

Applicants must be authorized to work in the U.S. without current or future sponsorship

Salary Range: 

$120,000 - $190,000.

In addition to base salary, this role will be eligible for a short-term incentive plan (performance-based bonus), subject to individual and company performance. 

The annual base salary range posted represents a broad range of salaries around the U.S. and is subject to many factors including but not limited to credentials, education, experience, geographic location, job responsibilities, performance, skills and/or training.

The successful candidate is expected to work in our NYC office 3 days per week and also be available for travel as required.

Interview Integrity Notice: Berkshire Hathaway GUARD is committed to a fair and consistent hiring process. Candidates are expected to participate independently in interviews. Unauthorized recording, transcription, AI note-taking, or AI interview assistance tools may not be used during interviews without prior approval.

Employment Type: FULL_TIME

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