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Remote Insurance Data Analytics Jobs in Mississippi

United Soccer League (USL)

$15 - $18.75/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

United Soccer League (USL)

$15.50 - $19.50/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

United Soccer League (USL)

$14 - $17.50/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

United Soccer League (USL)

$15.75 - $19.75/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

United Soccer League (USL)

$15.50 - $19.25/hr

Remote Overview of the United Soccer League (USL) The United Soccer League (USL) is the heartbeat ... The Participant will assume an integral role in the production of data analytics and distribution ...

Rebellion Defenses

Remote Operations Manager

Jackson, MS · Remote

$250K/yr

Monitor performance metrics and make data-driven decisions. * Collaborate with cross-functional ... Strong analytical and problem-solving skills. * Excellent communication and interpersonal abilities.

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All JobsInsurance Data Analytics JobsRemote Insurance Data Analytics JobsRemote Insurance Data Analytics Jobs in Mississippi

Remote Insurance Data Analytics information

What is remote insurance data analytics?

Remote insurance data analytics is the practice of analyzing insurance-related data, such as claims, risk assessments, and customer information, from a location outside of a traditional office setting. Professionals in this field use statistical methods, data mining, and machine learning tools to identify patterns, detect fraud, and help insurance companies make data-driven decisions. This remote role often requires proficiency in data analysis tools like SQL, Python, or R, and a strong understanding of insurance industry concepts. Remote insurance data analysts collaborate with teams virtually to provide insights and support business strategies, making it a flexible career option.

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

To excel in Remote Insurance Data Analytics, you need strong analytical skills, a background in statistics or mathematics, and typically a degree in data science, actuarial science, or a related field. Familiarity with data analysis tools like SQL, Python, R, and specialized insurance analytics platforms such as SAS or Tableau, as well as relevant certifications, is highly valuable. Attention to detail, problem-solving abilities, and effective communication set candidates apart in this role. These skills are crucial for transforming complex insurance data into actionable insights that drive informed business decisions and risk assessments.

How do remote insurance data analytics professionals typically collaborate with cross-functional teams to drive business insights?

Remote Insurance Data Analytics professionals often work closely with underwriters, actuaries, claims managers, and IT teams to gather data requirements, interpret findings, and implement data-driven solutions. Collaboration usually happens through virtual meetings, collaborative dashboards, and project management tools to ensure clear communication and alignment on objectives. This cross-functional approach helps identify trends, optimize risk assessments, and support strategic decision-making within the organization. Building strong relationships with team members across departments is key to successfully translating analytical results into actionable business strategies.

What is the difference between Remote Insurance Data Analytics vs Remote Insurance Underwriter?

AspectRemote Insurance Data AnalyticsRemote Insurance Underwriter
Required CredentialsBachelor's in Data Science, Statistics, or related field; often certifications in data analysis or analyticsBachelor's in Business, Finance, or related; often requires insurance licensing or certifications
Work EnvironmentPrimarily data analysis, modeling, and reporting; often collaborative with IT and actuarial teamsAssessing risks, reviewing applications, making underwriting decisions; involves communication with agents and clients
Employer & Industry UsageUsed across insurance companies, reinsurers, and brokers for data-driven decision makingUsed by insurance carriers to evaluate and approve policies

Remote Insurance Data Analytics focuses on analyzing insurance data to inform business decisions, while Remote Insurance Underwriters evaluate individual insurance applications to determine coverage. Both roles are essential in the insurance industry but differ in daily tasks and required skills.

What are the most commonly searched types of Insurance Data Analytics jobs in Mississippi?

The most popular types of Insurance Data Analytics jobs in Mississippi are:

What are popular job titles related to Remote Insurance Data Analytics jobs in Mississippi?

For Remote Insurance Data Analytics jobs in Mississippi, the most frequently searched job titles are:

What job categories do people searching Remote Insurance Data Analytics jobs in Mississippi look for?

The top searched job categories for Remote Insurance Data Analytics jobs in Mississippi are:

What cities in Mississippi are hiring for Remote Insurance Data Analytics jobs?

Cities in Mississippi with the most Remote Insurance Data Analytics job openings:

Remote Insurance Data Analytics jobs near you

Cheminformatics Specialist - Remote

micro1 AI

Jackson, MS • Remote

$80 - $110/hr

Part-time

Posted 17 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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