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Remote Applied Data Analytics Jobs in Bethlehem, PA

Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry. * Provide feedback and domain-specific insights to improve AI models in computational ...

BCABA Tutor

Allentown, PA ยท Remote

$18 - $40/hr

... data, and applying the BACB Ethics Code to professional scenarios. Emphasizes connecting theoretical principles to applied behavior analysis practice. * Curriculum Awareness & Adaptive Instruction:

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Remote Applied Data Analytics information

See Bethlehem, PA salary details

$24

$54

$93

How much do remote applied data analytics jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for remote applied data analytics in Bethlehem, PA is $54.09, according to ZipRecruiter salary data. Most workers in this role earn between $43.46 and $61.30 per hour, depending on experience, location, and employer.

What is remote applied data analytics?

A Remote Applied Data Analytics job involves analyzing data to extract insights and help organizations make data-driven decisions, all while working from a location outside of a traditional office. Professionals in this role use statistical methods, programming, and data visualization tools to interpret complex datasets. They often collaborate with cross-functional teams to solve business problems, optimize processes, and present actionable findings. Remote positions in this field require strong technical skills, good communication, and the ability to work independently using digital collaboration tools.

What are the key skills and qualifications needed to thrive as a remote applied data analytics professional?

To thrive as a Remote Applied Data Analytics professional, you need a strong background in statistics, data analysis, and problem-solving, typically supported by a degree in a quantitative field. Proficiency with data analytics tools such as Python, R, SQL, and visualization platforms like Tableau or Power BI, as well as familiarity with data management systems, is essential. Strong communication, self-motivation, and the ability to work independently are key soft skills for succeeding remotely and translating data insights into actionable recommendations. These skills ensure effective analysis, clear communication of findings, and the ability to drive data-informed decisions in a remote work environment.

What are some common challenges faced by professionals in remote applied data analytics roles, and how can they be addressed?

Remote applied data analytics professionals often encounter challenges such as effective communication with cross-functional teams, maintaining data security, and managing time across different time zones. To address these issues, it's important to leverage collaborative tools for clear communication, establish regular check-ins, and follow best practices for data privacy. Additionally, setting structured work hours and proactively aligning with teammates can help ensure smooth project workflows and successful outcomes.

What is the difference between Remote Applied Data Analytics vs Remote Data Analyst?

AspectRemote Applied Data AnalyticsRemote Data Analyst
Required CredentialsBachelor's in Data Science, Analytics, or related field; proficiency in analytics toolsBachelor's in Statistics, Mathematics, or related field; experience with data visualization tools
Work EnvironmentCollaborative teams, project-based tasks, often cross-functionalData-focused tasks, reporting, and data interpretation within organizations
Employer & Industry UsageTech, finance, healthcare, consulting firmsBusiness, marketing, finance, and healthcare sectors

Remote Applied Data Analytics involves applying advanced analytics techniques to solve complex problems, often requiring knowledge of data science tools. Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While both roles require analytical skills, Applied Data Analytics emphasizes modeling and predictive analytics, whereas Data Analysts concentrate on data interpretation and visualization.

What are popular job titles related to Remote Applied Data Analytics jobs in Bethlehem, PA?

For Remote Applied Data Analytics jobs in Bethlehem, PA, the most frequently searched job titles are:

What cities near Bethlehem, PA are hiring for Remote Applied Data Analytics jobs?

Cities near Bethlehem, PA with the most Remote Applied Data Analytics job openings:

Infographic showing various Remote Applied Data Analytics job openings in Bethlehem, PA as of June 2026, with employment types broken down into 95% Full Time, and 5% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $112,516 per year, or $54.1 per hour.

Director of Insurance Analytics

MSIG Holdings USA, Inc.

Warren, NJ โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 9 days ago


Job description

MSIG USA continues to grow!

Company Overview:

MSIG USA is the US-based subsidiary ofMS&AD Insurance Group Holdings, Inc., one of the world's top P&C carriers and a global Class 15 insurer, with A+ ratings and a reach that spans 40+ countries and regions. Leveraging our 350-year heritage, MSIG USA brings the financial strength, expertise, and global footprint to offer commercial insurance solutions that address your business's unique risks.

Summary/Job Purpose:

Part of the MS&AD group, a top-10 global P&C insurance carrier, MSIG USA is on a mission to become a data-driven leader in specialty insurance, focused on ambitious and profitable growth. Our Insurance Analytics function is at the heart of this transformation - delivering analytics and data science solutions that drive impact across Underwriting, Pricing, Claims, Actuarial and beyond.

We are seeking a hands-on analytics Manager/Director to lead a portfolio of high-impact initiatives, drive cross-functional delivery, and personally develop analytical solutions. This role is ideal for a builder-leader who thrives on both technical execution and stakeholder engagement.

You will lead the full analytics lifecycle end-to-end: problem framing and hypothesis definition, experimentation and modeling, and operationalization into repeatable decision support with monitoring and sustained adoption. Success is measured by measurable business outcomes, not slideware.

(Hybrid - 4 days in office; remote considered in exceptional circumstances)

Essential Functions

  • Lead a portfolio of analytics & data science initiatives
  • Own a portfolio of initiatives end-to-end: problem framing, prioritization, delivery planning, stakeholder alignment, and measurable business outcomes.
  • Translate ambiguous business questions into clear problem statements, hypotheses, and structured analytical approaches that influence decisions and operations.
  • Define success metrics and measurement plans (including benefit estimation) and track adoption and impact over time.
  • Drive cross-functional delivery across Underwriting, Pricing, Claims and Actuarial; ensure solutions are practical, adopted, and aligned to business priorities.
  • Partner closely with business leaders to align work to decision needs, manage tradeoffs transparently, and maximize impacts
  • Contribute directly by writing and reviewing code (Python & SQL), building analytical prototypes, reusable analytics assets, and decision-support tools, and unblocking technical decisions.
  • Apply statistical and machine learning techniques (e.g., regression, classification, clustering, time series) to solve business problems and support decision-making.
  • Develop and deploy solutions in a cloud-based analytics environment, partnering with platform and engineering teams to operationalize outputs into business workflows and drive sustained adoption.
  • Design and execute experiments and tests (as appropriate to the use case) to evaluate interventions, quantify impact, and support decision-making.
  • Define and reinforce production-minded practices and standards for analytical quality appropriate to the use case: validation, testing/controls, documentation, reproducible code, and operational transition plans for ongoing use.
  • Establish monitoring expectations appropriate to the solution (e.g., usage, data quality, and model performance) and drive continuous improvement based on signals.
  • Deliver decision support for Underwriting and Pricing/Actuarial
  • Lead and contribute to solutions that improve underwriting and pricing decisions (e.g., portfolio diagnostics, segmentation and feature development, workflow decision support), partnering closely with business leaders to drive adoption and measurable impact.
  • Support implementation into decisions and processes by educating stakeholders on model/analysis intent, limitations, and appropriate use, and by providing practical documentation and tooling.
  • Communicate findings clearly to both technical and non-technical audiences, and translate insights into concrete actions, process changes, or product improvements.
  • Partner with Claims leadership to identify and deliver high-value analytics and decision support opportunities that improve operational effectiveness and outcomes.
  • Support the data enablement needed for claims analytics in partnership with data and technology teams; translate claims workflows into analytics-ready measures and repeatable decision support and reporting.
  • Where applicable, help operationalize and monitor analytical solutions used in claims decisioning and workflows.
  • Serve as a trusted thought partner to senior stakeholders; communicate clearly, facilitate working sessions, and manage tradeoffs transparently.
  • Produce executive-ready narratives that connect analytical evidence to decisions, risks, and tradeoffs.
  • Mentor data scientists/analysts on problem structuring, technical approach, and effective communication.
  • Over time, help build the team through hiring, onboarding, and talent development as scope expands; responsibilities may evolve into formal people leadership.
  • Collaborate with technology and data platform teams to enable responsible deployment and operation of analytics solutions (access, security, maintainability, and monitoring expectations appropriate to the solution), without owning enterprise platforms.
  • Help define reusable patterns for analytics delivery (templates, review checklists, documentation standards) that reduce friction and improve time-to-value.

Supervisory Responsibilities:

  • This position is a hands-on program/initiative lead and may include people leadership. Scope and people-management responsibilities will vary by final level (Manager vs Director) and organizational needs.

Qualifications:

  • To perform this job successfully, an individual must be able to perform each essential duty. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Required Qualifications

  • Bachelor's degree in Statistics, Computer Science, Mathematics, Economics, or a related quantitative field or equivalent practical experience.
  • 7+ years of experience in analytics or data science, with a track record of delivering measurable business impact.
  • 2+ years leading analytics initiatives and/or mentoring technical team members in a senior/lead capacity.
  • Proficiency in Python and SQL; ability to write production-quality analytical code and review others' work.
  • Strong communication skills with ability to influence senior stakeholders; translate technical work into clear decisions, actions, and tradeoffs

Preferred Qualifications

  • Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field (or equivalent practical experience).Property & Casualty insurance experience (commercial lines preferred) or demonstrated ability to ramp quickly in complex domains.
  • Experience productionizing analytics/model outputs in partnership with engineering teams (e.g., APIs/services, CI/CD, containerization).
  • Experience with cloud-based analytics environments and modern ML frameworks (e.g., scikit-learn, XGBoost).
  • Experience with experimentation, causal inference, or rigorous measurement approaches in business settings.
  • Experience establishing monitoring practices appropriate to the solution (e.g., model performance, data quality, usage/adoption).
  • Familiarity with BI tools (Power BI, Tableau) and data visualization best practices.
  • Track record of mentoring, coaching, and/or managing technical teams.

#LI-HYBRID


Salary: The base pay range is $225,000.00 - $250,000.00 . Salary determinations are based on various factors, including but not limited to, relevant work experience, skills, certifications and location.
Additional Benefits:
Healthcare and Retirement Benefits
Comprehensive medical, dental, and vision coverage
401(k) with a generous employer match and profit-sharing contribution
Wellness incentive program
Life and accidental death and dismemberment (AD&D) insurance
Flexible spending programs
Short-term and long-term disability plans
Additional Benefit Programs
Paid time off program
Paid charitable leave
Paid parental leave
Tuition reimbursement program
Personal insurance (auto/homeowners) discounts

It's an exciting time for our company and a great opportunity to join a financially sound and growing global insurance group!


It is the policy of MSIG USA to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, MSIG USA will provide reasonable accommodations for qualified individuals with disabilities.