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

Snorkel AI

Lead Data Scientist

New York, NY · On-site +1

$130K - $200K/yr

Critical-path data science projects * 20% : Partnering with Engineers, PMs, DaaS operational leads, and Finance What You'll Do * Own Generative AI Analytics: Build and maintain end-to-end infra ...

TickPick

Data Scientist

New York, NY · On-site +1

BA/BS in a quantitative field such as Statistics, Computer Science, Engineering, Mathematics, or ... A hybrid in-office approach, enabling remote work a portion of each week * Health Care Plan ...

Carlyle

AlpInvest Embedded Data Scientist

New York, NY · On-site +1

$180K - $200K/yr

Join our dynamic Investment Data Science Team as an Embedded Data Scientist to partner directly with investment professionals across Primaries, Secondaries, and Co-Investments. This role sits at the ...

Bayer

Associate Dir, Full Stack Data Scientist

Whippany, NJ · On-site +1

$59K - $59K/yr

Remote work arrangements will not be accommodated for this role. YOUR TASKS AND RESPONSIBILITIES ... Extensive experience in Data Science capability assessment and analysis; Demonstrated ability to ...

Bayer

Associate Dir, Full Stack Data Scientist

Whippany, NJ · On-site +1

$59K - $59K/yr

Remote work arrangements will not be accommodated for this role.YOUR TASKS AND RESPONSIBILITIES ... Extensive experience in Data Science capability assessment and analysis;Demonstrated ability to ...

PortPro

Data Scientist

New York, NY · Remote

Experience with data science toolkits, such as NumPy, Pandas, Matplotlib. * Familiarity with Big Data tools and platforms, such as Hadoop, Spark, or similar. * Strong analytical skills with the ...

PortPro

Data Scientist

New York, NY · On-site +1

Experience with data science toolkits, such as NumPy, Pandas, Matplotlib. * Familiarity with Big Data tools and platforms, such as Hadoop, Spark, or similar. * Strong analytical skills with the ...

Smarsh

Lead Data Scientist

New York, NY · On-site +1

Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...) * Strong knowledge of key programming concepts (e.g. split ...

Pinterest Job Advertisements

Sr. Data Scientist

New York, NY · On-site +1

$226K - $287K/yr

Telecommuting and/or remote employment permitted. Minimum Requirements: Master's degree (or a foreign equivalent) in Finance, Data Science, or a related field and three (3) years of experience in the ...

Hang

Data Scientist

New York, NY · On-site +1

Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field. * 5-10+ years of proven experience as a Data Scientist or in a similar role. * Strong knowledge of ...

OpenX

Staff Data Scientist

New York, NY · Remote

$195K - $218K/yr

Identify and lead high-impact, cross-team data science initiatives, such as improving bidding strategies, building new prediction systems, or redesigning experimentation frameworks * In partnership ...

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Showing results 21-40

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

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.

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).

Can I work remotely as a remote data scientist?

Yes, many remote data scientist positions are available, allowing professionals to work from anywhere with a reliable internet connection. These roles often require skills in programming, data analysis, and familiarity with tools like Python, R, or SQL, and may involve collaboration through online platforms. Remote work arrangements are common in the data science field, especially with the increasing adoption of cloud-based tools and flexible schedules.

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.

More about Remote Data Science jobs
What are the most commonly searched types of Data Science jobs in Hoboken, NJ? The most popular types of Data Science jobs in Hoboken, NJ are:
What are popular job titles related to Remote Data Science jobs in Hoboken, NJ? For Remote Data Science jobs in Hoboken, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Hoboken, NJ look for? The top searched job categories for Remote Data Science jobs in Hoboken, NJ are:
What cities near Hoboken, NJ are hiring for Remote Data Science jobs? Cities near Hoboken, NJ with the most Remote Data Science job openings:
Remote Data Science jobs near you
Infographic showing various Remote Data Science job openings in Hoboken, NJ as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 17% Part Time, 3% Temporary, and 5% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data Science and Machine Learning Engineer

1 point system

New York, NY • Remote

Contractor

Re-posted 25 days ago

Job description

Job Summary:

  • We are seeking a Senior Data Science Engineer to design, build, and scale data-driven systems that power advanced analytics and machine learning across our organization. This role sits at the intersection of software engineering and data science; you’ll be responsible for building robust data pipelines, enabling experimentation, and deploying production-ready machine learning models.
  • As a senior team member, you will mentor junior engineers and data scientists, influence architectural decisions, and help shape the long-term AI and data strategy.

Key Responsibilities:

  • Develop, deploy, and maintain machine learning models in production environments.
  • Collaborate with data scientists, analysts, and product managers to define and deliver data-driven features.
  • Ensure high-quality data through monitoring, validation, and robust testing frameworks.
  • Architect and maintain data platforms and tools for experimentation, model serving, and feature engineering.
  • Explore and integrate Large Language Models (LLMs) and other generative AI approaches into business applications and data workflows.
  • Contribute to code reviews, technical design discussions, and best practices for the team.
  • Mentor and guide junior engineers/data scientists, fostering technical excellence and career growth.
  • Stay current with emerging technologies in Data Science, Machine Learning, LLM Ops, ML Ops.

Education Requirement:

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • Master’s degree or PhD is a strong plus.

Experience:

  • 5+ years of experience in data engineering, machine learning engineering, or related roles.
  • Strong proficiency in Python (Pandas, NumPy, PySpark, or similar).
  • Solid understanding of ML model development, training, and deployment pipelines.
  • Experience with ML model monitoring and observability frameworks.
  • Experience with deep learning frameworks(TensorFlow, PyTorch).
  • Familiarity with CI/CD, version control (Git),and modern ML Ops practices.