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Remote Meta Data Science Jobs in Missouri (NOW HIRING)

Jobgether

$159K - $215K/yr

... data science, and fraud prevention. You will lead a multidisciplinary team responsible for ... Fully remote work environment with a globally distributed team. * Opportunity to lead a ...

Jobgether

This role offers an opportunity to combine biological science, data management, and digital ... Europe-remote working arrangement. * International and multidisciplinary working environment.

Kohl's

$95K - $131K/yr

Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113K - $136K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data ... Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent ...

GRVTY

Technical Scientist - SME

Springfield, MO · On-site +1

$150K - $235K/yr

... image science methods, and multi-platform remote sensing analytics. The work is fast-paced and ... Analyze optical signature data to extract target phenomenology, characterize signatures, and ...

Meridial

$8 - $65/hr

With high-quality training data, tomorrow's AI can democratize world-class education, keep pace ... Remote Seniority level: Mid - Senior Level

Solventum

Medical Science Specialist

Saint Louis, MO · On-site +1

$187K - $257K/yr

You will be responsible for communicating complex clinical data, supporting investigator-initiated ... Remote USA Travel: May include up to 75 % Relocation Assistance: Not authorized Pay Transparency ...

Jobgether

You will take end-to-end responsibility for Meta and TikTok performance, from budget allocation and ... The role combines strategic ownership with daily execution in a fast-moving, data-driven ...

New

Kohl's

$112K - $148K/yr

Collaborate with stakeholders, data scientists, and full stack engineers to deliver trusted, documented, and reusable data products What Skills You Have Required * 4+ years of experience in software ...

Third-Party Job Posts

Location - Remote (Europe) How You'll Make an Impact: As a Staff Machine Learning Engineer , you ... We thrive on collaborative innovation, where data scientists, engineers, and product experts ...

All Generation Tech

Data Engineer-US

Columbia, MO · On-site +1

$109K - $130K/yr

Columbia, MO (Hybrid - 1 week in office, 1 week remote) Experience: 4+ years Schedule: Full-time, ... Bachelor's or Master's degree in Computer Science, Information Systems, or a related field is ...

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All JobsMeta Data Science JobsRemote Meta Data Science JobsRemote Meta Data Science Jobs in Missouri

Remote Meta Data Science information

What is a remote meta data scientist?

A Remote Meta Data Scientist is a professional who works for Meta (formerly Facebook) in the field of data science, but does so from a remote location instead of a traditional office. They analyze large datasets, build predictive models, and provide insights to help Meta improve its products and user experience. Their work may involve machine learning, statistical analysis, and collaborating virtually with cross-functional teams. Remote Meta Data Scientists use tools such as Python, SQL, and data visualization software to solve complex business problems.

How does a remote meta data science role typically collaborate with cross-functional teams despite being off-site?

In a remote Meta Data Science position, collaboration with cross-functional teams—such as product managers, engineers, and designers—is primarily facilitated through virtual communication tools like video conferencing, chat platforms, and collaborative project management software. Regular stand-ups, sprint meetings, and asynchronous updates help ensure alignment on project goals and timelines. While remote work offers flexibility, it also requires proactive communication and documentation to maintain transparency and foster effective teamwork. Building relationships remotely may take extra effort, but companies like Meta provide structured onboarding and virtual community events to support team cohesion.

What are the key skills and qualifications needed to thrive as a remote meta data scientist, and why are they important?

To thrive as a Remote Meta Data Scientist, you need strong analytical skills, expertise in statistics and machine learning, and a degree in a quantitative field such as computer science or mathematics. Proficiency with data science tools like Python, R, SQL, and platforms such as TensorFlow or PyTorch is typically required, along with experience using collaboration tools for remote work. Excellent communication, self-motivation, and problem-solving abilities are essential soft skills for remote collaboration and translating insights to stakeholders. These skills ensure you can independently deliver impactful data-driven solutions while effectively collaborating across distributed teams.

What is the difference between Remote Meta Data Science vs Remote Data Analyst?

AspectRemote Meta Data ScienceRemote Data Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's degree in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative remote teams, often with data science and engineering departmentsRemote work with focus on data reporting, visualization, and business insights
Employer & Industry UsageTech companies, e-commerce, finance, and healthcareMarketing agencies, retail, finance, and consulting firms

Remote Meta Data Science involves advanced data modeling, machine learning, and statistical analysis, often requiring programming skills and a strong technical background. Remote Data Analysts focus on interpreting data, creating reports, and visualizations to support business decisions. While both roles work remotely and require data handling skills, Meta Data Scientists typically engage in more complex modeling, whereas Data Analysts concentrate on data interpretation and presentation.

What are the most commonly searched types of Meta Data Science jobs in Missouri?

The most popular types of Meta Data Science jobs in Missouri are:

What are popular job titles related to Remote Meta Data Science jobs in Missouri?

For Remote Meta Data Science jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Remote Meta Data Science jobs in Missouri look for?

The top searched job categories for Remote Meta Data Science jobs in Missouri are:

What cities in Missouri are hiring for Remote Meta Data Science jobs?

Cities in Missouri with the most Remote Meta Data Science job openings:

Remote Meta Data Science jobs near you
Infographic showing various Remote Meta Data Science job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Engineering Manager, Identification Accuracy

Jobgether

On-site, Remote

$159K - $215K/yr

Full-time

Posted 25 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engineering Manager, Identification Accuracy based in Netherlands.

This is a high-impact engineering leadership role at the intersection of machine learning, data science, and fraud prevention. You will lead a multidisciplinary team responsible for improving the accuracy and reliability of a critical identification platform. The role combines people leadership, technical strategy, and hands-on program direction in a globally distributed, fully remote environment. You'll shape the team roadmap and guide the development of production ML systems operating at massive scale. Working closely with engineering, product, and customer-facing teams, you'll translate business needs into meaningful technical priorities. This is an opportunity to influence both the technology and the people behind a best-in-class fraud detection capability.

Accountabilities
  • Lead and grow a multidisciplinary Identification Accuracy team spanning ML engineers, data scientists, analysts, and analytics engineers, fostering psychological safety, technical excellence, accountability, and continuous improvement.
  • Own the team's technical roadmap in collaboration with senior engineering leadership and cross-functional stakeholders, identifying opportunities to improve model quality and address complex identification challenges.
  • Drive measurable model accuracy outcomes by enabling the team to design, train, evaluate, and deploy machine learning models that improve identification performance across billions of devices.
  • Oversee the delivery of production ML systems across data pipelines, feature engineering, model development, evaluation, and deployment, ensuring reliability and scalability.
  • Partner closely with platform and API engineering teams to understand downstream requirements, performance expectations, and latency constraints.
  • Collaborate with Product and customer-facing teams to translate customer needs and business priorities into technical initiatives and product improvements.
  • Communicate model performance, data-quality considerations, technical trade-offs, risks, and roadmap priorities clearly to both technical teams and senior business stakeholders.
  • Build a high-performing, multidisciplinary organization by mentoring team members, developing technical leaders, and creating an environment where people can do their best work.
  • Continuously improve engineering and ML practices, including experimentation, model evaluation, MLOps, data workflows, and operational processes.
Requirements
  • 5+ years of professional experience in software engineering, machine learning, data science, or a related technical discipline, including at least 2 years leading an ML or data science team in a fast-paced environment.
  • Proven experience managing technical teams that deliver production machine learning systems, from data pipelines and feature engineering through model training, evaluation, and deployment.
  • Demonstrated success building and developing high-performing multidisciplinary teams that include engineers, data scientists, analysts, or analytics engineers.
  • Strong technical understanding of machine learning and data systems, with familiarity with MLOps practices and tooling such as experiment tracking, feature stores, model registries, and ML CI/CD pipelines.
  • Experience working with large-scale behavioral or event data in production environments.
  • Hands-on familiarity with data stack and analytics engineering technologies such as dbt or similar tools.
  • Ability to work effectively with platform and API engineering teams and understand technical requirements, system dependencies, and latency constraints.
  • Excellent written and verbal communication skills, with the ability to translate complex model behavior, data-quality challenges, and technical trade-offs for both technical and non-technical audiences.
  • Demonstrated ability to deliver results in rapidly scaling environments where priorities evolve and ambiguity is part of the work.
  • Strong people leadership skills, including coaching, mentoring, team development, and fostering a culture of psychological safety and high performance.
  • Experience in fraud detection, identity, trust & safety, or a related domain is a plus, but not required.
  • Must be authorized to work from Poland; visa sponsorship is not available for this role.
Benefits
  • Competitive compensation package; for US-based employees, the stated cash compensation range is $159,000-$215,000 USD, while compensation for Poland and other locations may vary according to local market benchmarks.
  • Fully remote work environment with a globally distributed team.
  • Opportunity to lead a multidisciplinary ML and data organization solving challenging problems at significant scale.
  • Exposure to cutting-edge machine learning, fraud detection, identity, and data technologies.
  • High level of autonomy and meaningful influence over technical strategy, team development, and product outcomes.
  • Inclusive environment that values diverse experiences, perspectives, and backgrounds.
  • Opportunity to work on technology used by major enterprises and high-growth companies worldwide.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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