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

USM

JB061757 - HEDIS Data Analyst (SQL)

Philadelphia, PA · On-site +1

Philadelphia ,PA - Hybrid - 3 Days a week in the office/ Remote Duration: Long-Term Contract Job ... Bachelor's degree in Computer Science, Information Systems, Healthcare Informatics, Data Analytics ...

SITA Switzerland Sarl

Data Engineer

Cedar Brook, NJ · On-site +1

$113K - $136K/yr

Partner closely with Back-End and Science teams so product features and algorithms are built on reliable data * Work on several airline integrations in parallel, accelerating client onboarding and ...

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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 job categories do people searching Remote Data Science jobs in Sicklerville, NJ look for?

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

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

Remote Data Science jobs near you

JB061757 - HEDIS Data Analyst (SQL)

USM

Philadelphia, PA • On-site, Remote

Contractor

Re-posted 3 days ago

Job description

  • Start Date: Interview Types
  • Skills Healthcare Effective.. Visa Types US Citizen

    • Job Title: HEDIS Data Analyst (SQL)
    Location: Philadelphia ,PA - Hybrid - 3 Days a week in the office/ Remote
    Duration: Long-Term Contract
    Job Summary
    We are seeking a detail-oriented HEDIS Data Analyst with strong SQL skills to support Healthcare Effectiveness Data and Information Set (HEDIS) reporting, quality improvement initiatives, and healthcare data analysis. The ideal candidate will have experience working with healthcare data, analyzing HEDIS measures, validating data accuracy, and developing SQL queries to support reporting, compliance, and performance improvement.
    Key Responsibilities
    • Analyze and validate HEDIS (Healthcare Effectiveness Data and Information Set) measures to support quality improvement and regulatory reporting.
    • Develop, write, optimize, and maintain complex SQL queries for healthcare data extraction, validation, and reporting.
    • Perform data analysis to identify trends, gaps in care, and opportunities for quality improvement.
    • Validate data accuracy and ensure compliance with HEDIS specifications and organizational standards.
    • Collaborate with quality, clinical, business, and IT teams to support HEDIS reporting initiatives.
    • Perform data reconciliation, quality assurance, and root cause analysis of data discrepancies.
    • Support annual HEDIS submission activities, including data validation and audit preparation.
    • Create reports, dashboards, and data summaries to support leadership decision-making.
    • Monitor data quality and recommend process improvements to improve reporting accuracy.
    • Document SQL queries, data mapping, business rules, and reporting processes.
    • Assist with troubleshooting data issues and resolving reporting discrepancies.
    • Ensure compliance with HIPAA and healthcare data privacy regulations.

    Required Qualifications
    • Bachelor's degree in Computer Science, Information Systems, Healthcare Informatics, Data Analytics, or a related field (or equivalent experience).
    • 3+ years of experience working with HEDIS reporting or healthcare quality data.
    • Strong hands-on experience writing and optimizing SQL queries.
    • Experience analyzing large healthcare datasets.
    • Knowledge of HEDIS measures, quality reporting, and healthcare data standards.
    • Strong analytical, problem-solving, and data validation skills.
    • Excellent communication and documentation skills.

    Preferred Qualifications
    • Experience with managed care, health plans, or payer organizations.
    • Familiarity with NCQA HEDIS specifications and reporting guidelines.
    • Experience with healthcare data warehouses and reporting tools.
    • Knowledge of claims, provider, member, and clinical data.
    • Experience with ETL processes and data integration.
    • Experience with BI tools such as Power BI, Tableau, or SSRS.

    Required Skills
    • HEDIS (Healthcare Effectiveness Data and Information Set)
    • SQL
    • Database Querying
    • Healthcare Data Analysis
    • Data Validation
    • Data Quality
    • Reporting & Analytics
    • Healthcare Quality Measures
    • Claims Data Analysis
    • Clinical Data Analysis
    • NCQA HEDIS Guidelines
    • Data Reconciliation
    • Root Cause Analysis
    • Dashboard Development
    • HIPAA Compliance
    • Microsoft SQL Server / Oracle / PostgreSQL (as applicable)
    • Problem Solving
    • Documentation
    • Healthcare Informatics
    Quality Improvement

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