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Data Jobs (NOW HIRING)

Data Center Project Manager

Cincinnati, OH ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Data Center Project Manager

Nashville, TN ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Data Center Project Manager

Englewood, CO ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Data Center Project Manager

Nashville, TN ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Data Center Project Manager

Sunnyvale, CA ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Data Center Project Manager

La Vista, NE ยท On-site

$125K - $130K/yr

Ensure the effective and economical use of H5 Data Center's business resources, and to support the financial requirements of the operation at the Data Center facilities. Works to make sure proper ...

Showing results 41-60

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$46K

$165K

$243.5K

How much do data jobs pay per year?

As of Aug 19, 2026, the average yearly pay for data in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What are different jobs that work with data?

Many different jobs require you to work with data. Occupational health and safety engineers, for instance, assess safety data collected by technicians and specialists and then design new processes to mitigate observed risks. Many careers in medical research, such as running clinical trials or developing new pharmaceuticals, require data collection and analysis. A large number of government labor and economic forecasting positions employ statisticians who analyze and model data based on surveys or raw information, such as the census or employment records.

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

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with data analysis tools like Excel, SQL, Python, and visualization platforms such as Tableau or Power BI is often required, and certifications in these tools can be advantageous. Attention to detail, critical thinking, and effective communication skills help analysts interpret data accurately and present actionable insights to stakeholders. These skills are crucial for transforming raw data into meaningful information that drives informed business decisions.

How does a data analyst typically collaborate with other departments within an organization?

Data Analysts frequently work cross-functionally, partnering with teams such as marketing, finance, operations, and product development. They gather requirements from stakeholders, interpret data to provide actionable insights, and often present findings in meetings or reports tailored to the audience's needs. Effective communication is key, as analysts must translate complex data into clear, impactful recommendations that guide business decisions. This collaborative environment fosters both learning and professional growth, as Data Analysts gain exposure to various business functions.

What is the difference between Data vs Data Analyst?

AspectDataData Analyst
Required CredentialsTypically a degree in computer science, information technology, or related fieldsSame as Data, often requiring a degree in statistics, data science, or related areas
Work EnvironmentData professionals work in IT, data engineering, or database management settingsData analysts work in business, finance, marketing, and similar industries analyzing data for insights
Employer & Industry UsageUsed across tech, finance, healthcare, and more for data management and infrastructureCommonly employed in business sectors to interpret data and support decision-making

Data professionals focus on managing, storing, and processing data, while Data Analysts interpret and analyze data to generate insights. Both roles require similar educational backgrounds but differ in their primary functions within organizations.

What are careers in data?

Careers in data include roles such as data analyst, data scientist, data engineer, and database administrator. These jobs involve collecting, analyzing, and managing data using tools like SQL, Python, and data visualization software, often requiring strong analytical skills and knowledge of data management principles.

What data jobs are there?

Data jobs include roles such as data analyst, data scientist, data engineer, and database administrator. These positions typically require skills in programming, statistics, and data management tools like SQL, Python, or R, and may involve working with large datasets, data visualization, and machine learning techniques.

What cities are hiring for Data jobs?

Cities with the most Data job openings:

What are the most commonly searched types of Data jobs?

The most popular types of Data jobs are:

What states have the most Data jobs?

States with the most job openings for Data jobs include:

Infographic showing various Data job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Senior Data Scientist / Analyst, Risk

Unchain Data

Manhattan, NY โ€ข On-site

$150 - $210/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New


Job description

About Polymarket

Polymarket is the world's fastest growing prediction market. We enable individuals to express views on real-world events by trading on outcomes across politics, economics, sports, culture, and current affairs. Built as a peer-to-peer marketplace with no centralized \"house,\" Polymarket aggregates diverse opinions into transparent, market-based probabilities that reflect collective expectations about the future.

We're growing fast, both in terms of volume ($115B traded to date) and adoption as an alternative news source. Our ambition is to become a ubiquitous beacon of truth in global media and we need your help adding fuel to the fire.

About the Role

Polymarket is looking for a Senior Data Scientist / Analyst, Risk to find the patterns that indicate abuse on our platform: fake and duplicate signups, farmed bonuses, collusive or manipulative trading, etc, and to turn what you find into controls that hold. You'll work closely with product and compliance, sitting between the data and the decisions about who gets to trade and under what conditions.

This is a role for someone who enjoys adversarial problems. The behavior you're looking for is actively trying not to be found, and the signal is usually in how accounts act together rather than in any single field. You'll be expected to build the detection, quantify the exposure, and make a clear recommendation about what to do about it. And you'll do it in a fast-moving environment where every new product opens new abuse vectors.

What You'll Do
  • Investigate and quantify abuse across the funnel, including multi-accounting and fake signups, bonus and promotion farming, wash trading, collusion, and market manipulation

  • Build detection logic that separates genuine users from coordinated behavior, combining on-chain, device, and behavioral signals rather than relying on any one of them

  • Turn one-off investigations into monitoring, including recurring reporting and alerting that surfaces new patterns without someone having to go looking

  • Size the financial exposure of each abuse vector so the team can prioritize by what it actually costs rather than by how alarming it looks

  • Partner with product on controls at the points of friction: onboarding, verification, bonus eligibility, and measure whether they worked without driving away legitimate users

  • Support compliance with the analysis behind investigations, escalations, and regulatory reporting

  • Work with analytics engineers to promote your detection logic into the modeled layer so it runs reliably instead of living in a notebook

  • Own documentation end-to-end - including the thresholds and rationale behind your detection logic, written clearly enough that compliance or any engineer can follow it without you in the room

What We're Looking For
  • 7+ years in risk, fraud analytics, trust and safety, or a similar investigative analytical role

  • Expert SQL. You can pursue a hypothesis across large behavioral datasets without supervision

  • Pattern recognition instinct. You can look at a cluster of accounts and articulate what they share and why it is unlikely to be coincidence

  • Experience building detection rules or models, and honesty about the tradeoff between false positives and missed abuse

  • Sound judgment about user impact. You understand that every control has a cost to legitimate users, and you can weigh the two

  • Comfort working alongside compliance, and the discretion to handle sensitive findings appropriately

  • Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace

  • (Plus) Experience with on-chain analysis, wallet clustering, or blockchain forensics

  • (Plus) Experience with trade surveillance, market manipulation detection, or AML

  • (Plus) Statistical or machine learning background - anomaly detection, graph analysis, or clustering in Python or R

  • (Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products

Benefits
  • Competitive salary & equity

  • Unlimited PTO

  • Full Health, Vision, & Dental coverage

  • 401k match

  • Hardware setup: new MacBook Pro, big display, & accessories

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