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

Dlapiper

Data Scientist

Short Hills, NJ · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

Dlapiper

Data Scientist

New York, NY · On-site +1

Prioritizes, scopes and manages data science projects for internal stakeholders and clients ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

MM International

Data Scientist

New York, NY · Remote

Remote Duration 4-6 months The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined ...

Mercor

Senior Data Scientist - F500 Expert

New York, NY · Remote

$60 - $70/hr

Remote Role Responsibilities * Construct enterprise data science scenarios for large-scale predictive modeling , multi-stakeholder analytics governance , and complex data infrastructure decisions at ...

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 ...

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 +1

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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Showing results 21-40

All JobsData Science JobsRemote Data Science JobsRemote Data Science Jobs in Chatham, NJ

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 Chatham, NJ?

The most popular types of Data Science jobs in Chatham, NJ are:

What are popular job titles related to Remote Data Science jobs in Chatham, NJ?

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

What cities near Chatham, NJ are hiring for Remote Data Science jobs?

Cities near Chatham, NJ with the most Remote Data Science job openings:

Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Chatham, NJ as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior Cybersecurity Data Science & Analytics Lead (Remote)

TSG Risk Management

New York, NY • Remote

Full-time

Posted 5 days ago

Job description

Location: New York City preferred. Candidates located near other major offices, including Charlotte, NC, Los Angeles, CA, and Southern California, will also be considered. Remote candidates are welcome to apply but should be open to periodic travel, potentially once per month, to New York City or another company office.

Work Model: Flexible hybrid or remote

Position Overview

We are seeking a senior-level Cybersecurity Data Science and Analytics Lead to help shape and scale how security data is used across the organization.

This role goes beyond building dashboards. The ideal candidate will partner directly with cybersecurity subject matter experts to understand complex security challenges, frame the right analytical questions, and develop solutions that provide meaningful, actionable insights.

The successful candidate will bring a strong combination of cybersecurity domain knowledge, data science experience, product thinking, and the ability to lead work independently. This individual should be comfortable challenging assumptions, recommending solutions, and translating security needs into scalable analytical products.

Responsibilities

  • Partner with cybersecurity and technology stakeholders to identify, frame, and solve complex analytical problems.
  • Translate security challenges into clear data science, analytics, and engineering solutions.
  • Develop analytical products that support meaningful business and security decisions.
  • Move beyond traditional dashboard delivery by creating reusable data products, self-service capabilities, and scalable analytical solutions.
  • Help determine the best delivery model for security analytics, including dashboards, reusable datasets, advanced analytics, and potential AI-enabled solutions.
  • Provide analytical support across application security and infrastructure security domains.
  • Evaluate security data and determine the appropriate analysis, methodology, and delivery approach.
  • Build trusted relationships with security subject matter experts through practical, applied cybersecurity knowledge.
  • Lead projects independently and take ownership of solutions from initial problem definition through delivery.
  • Communicate findings, recommendations, and technical decisions clearly to technical teams and senior leadership.
  • Contribute to the continued development of the organization's cybersecurity data and analytics strategy.

Required Qualifications

  • Approximately 10 or more years of relevant professional experience, with flexibility based on the depth and quality of the candidate's background.
  • Strong applied cybersecurity experience, particularly within application security and infrastructure security.
  • Advanced data science, analytics, or statistical analysis experience.
  • Experience working with CI/CD toolchains and secure software development lifecycle practices.
  • Knowledge of SaaS and data-as-a-service environments.
  • Experience with cloud-native monitoring and security tools.
  • Familiarity with endpoint protection technologies.
  • Ability to work with security data, frame analytical problems, and determine the appropriate analysis or solution.
  • Experience developing scalable analytical products rather than only producing one-time reports or dashboards.
  • Strong communication and stakeholder-management skills.
  • Ability to work independently, take ownership, and lead projects with limited direction.
  • Experience presenting technical findings and recommendations to leadership.

Preferred Qualifications

  • Experience designing reusable data products or self-service analytics capabilities.
  • Experience applying AI or machine learning to analytics or cybersecurity use cases.
  • Background supporting enterprise information security or CISO organizations.
  • Experience working across cybersecurity engineering and data science teams.
  • Product management or analytical product development experience.
  • Knowledge of security data associated with cloud platforms, applications, infrastructure, and endpoints.