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

... remote locations. ** About our Team : LexisNexis Legal & Professional, serving customers in over ... Define and execute the data science vision and roadmap aligned with business objectives and ...

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.

You will be designing analytical frameworks, developing data science products, and uncovering ... City, NY (remote), and Seattle, WA (remote). Candidates must permanently reside in the US ...

Remote (10% Travel to Sunnyvale, CA) Salary: $75.00-$80.00/Hourly Role: Data Scientist Specialist Primary Skills: AI/ML Role Description: The Data Scientist Specialist must have 8+ years of ...

Data Science Experts Type: Contract Compensation: $70-$100/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams on data science methodology ...

New York, NY or Secaucus, NJ (Hybrid) Decision Science Engineer (Applied Data Scientist) POSITION SUMMARY: Alice + Olivia is hiring a Decision Science Engineer to build, operationalize, and own ...

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 ...

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 ...

Company Insight: A leading global investment firm is expanding its sector-focused data science ... Please do not apply if you are looking for a contract or remote work * Please ensure you meet the ...

AI and Data Science Engineer III

Morristown, NJ · On-site +1

$117K - $141K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms, drives innovation, and helps make a significant impact on our clients' success. We ...

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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.
What are the most commonly searched types of Data Science jobs in Secaucus, NJ? The most popular types of Data Science jobs in Secaucus, NJ are:
What are popular job titles related to Remote Data Science jobs in Secaucus, NJ? For Remote Data Science jobs in Secaucus, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Secaucus, NJ look for? The top searched job categories for Remote Data Science jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Remote Data Science jobs? Cities near Secaucus, NJ with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Secaucus, NJ as of June 2026, with employment types broken down into 2% As Needed, 72% Full Time, 24% Part Time, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Director, Data Sciences

LexisNexis

New York, NY • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 hours ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

149th of 427 rated business services


Job description

** Please note that the selected individual for this role will be expected to work in our Raleigh, NC location from the time of joining. If you reside outside of the Raleigh region and you are unable or unwilling to relocate, then please consider other roles across our organization that might allow for remote locations. **

About our Team:

LexisNexis Legal & Professional, serving customers in over 150 countries with 11,800 employees worldwide, is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. Our company is a leader in deploying AI and advanced technologies to improve productivity and transform the legal market. We prioritize using the best models from today's top creators for each legal use case.

About the Role:

The Director, Data Sciences raises data-driven decision making of a function within a business unit through team leadership. They are also client/industry-facing, and they evangelize methodologies and best practices. They lead people and teams to develop an overall strategy for the execution of projects including creating use cases, roadmaps, alignment of stakeholders, and prioritization. This person acts as coach and leader of Managers and Data Scientists, as well as other resources. Influence should extend outside the director's immediate team to other teams within the director's peers. The Director drives development and implementation across the team to the business, rooted in a deep understanding of our customers, markets, trends, and challenges.

Responsibilities:

  • Strategic Leadership: Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.

  • Team Management: Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.

  • Advanced Research Direction: Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage. Champion innovation by staying current with the latest trends and techniques in data science and allocating resources to promising new approaches.

  • Machine Learning and AI Solutions: Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems. Data Analysis and Modeling: Oversee advanced data analysis, modeling, and machine learning to develop predictive and prescriptive models that drive business outcomes.

  • Data Collection and Preparation: Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.

  • Data Visualization Strategy: Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.

  • Cross-functional Collaboration: Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.

  • Model Deployment and MLOps: Oversee the deployment of machine learning models into production environments, ensuring scalability and reliability.

  • Documentation Standards: Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.

  • Stakeholder Management: Communicate the value and impact of data science initiatives to C-suite executives and business stakeholders.

  • Budget and Resource Management: Manage departmental budget, resource allocation, and infrastructure needs for data science operations.

  • Ethical AI Governance: Develop and enforce ethical guidelines and best practices for AI development and deployment.

Requirements:

  • Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.

  • 10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.

  • Demonstrated experience in managing and scaling data science teams of 15+ professionals.

  • Proven record of delivering high-impact AI and ML solutions that have driven significant business value.

  • Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.

  • Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.

  • Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.

  • Strong business acumen with the ability to translate complex technical concepts into business value.

  • Excellent communication and leadership skills, with experience presenting to executive leadership.

  • Experience working in a global or multicultural environment

  • Record of successful collaboration with product, engineering, and business teams.

  • Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.

Work in a way that works for you:

We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

Working for you:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

  • Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits

  • Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan

  • Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs

  • Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity

  • Family Benefits, including bonding and family care leaves, adoption, and surrogacy benefits

  • Health Savings, Health Care, Dependent Care and Commuter Spending Accounts

  • Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

About the Business:

LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services.

#AIFluency

U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Formor please contact 1-855-833-5120.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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