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Data 400K Jobs (NOW HIRING)

Triumph

Data Scientist

San Francisco, CA · On-site

$200K - $400K/yr

The Role As a Data Scientist, you'll own the quantitative systems that drive how millions of real ... Compensation Range: $200K - $400K

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GenAI Account Executive

Manhattan, NY · Remote

$200K - $400K/yr

Manhattan, NY (Remote) Salary: $200K - $400K/yr Type: Full‐time Posted: 18 hours ago What You'll ... Data services as strategic solutions Work closely with solutions and delivery teams during ...

Actively AI

Strategic Account Executive

Manhattan, NY · On-site

$300K - $340K/yr

This is a high-impact, full-cycle role focused on $400K+ enterprise deals. You will operate at ... Additionally, Actively AI leverages current market data to determine compensation, so posted ...

Actively AI

Strategic Account Executive

San Francisco, CA · On-site

$300K - $340K/yr

This is a high-impact, full-cycle role focused on $400K+ enterprise deals. You will operate at ... Additionally, Actively AI leverages current market data to determine compensation, so posted ...

Actively AI

Strategic Account Executive

New York, NY · On-site

$300K - $340K/yr

This is a high-impact, full-cycle role focused on $400K+ enterprise deals. You will operate at ... Additionally, Actively AI leverages current market data to determine compensation, so posted ...

Actively AI

Strategic Account Executive

San Francisco, CA · On-site

$300K - $340K/yr

This is a high-impact, full-cycle role focused on $400K+ enterprise deals. You will operate at ... Additionally, Actively AI leverages current market data to determine compensation, so posted ...

Together For Talent

VP of Sales

Atlanta, GA

$170K - $190K/yr

Lead complex, multi-stakeholder deals in the $400K-2M+ range from pipeline to close. * Define and ... Maintain tight CRM discipline, forecasting accuracy, and data-driven decision making. What You ...

Actively AI

Strategic Account Executive

San Francisco, CA · On-site

$300K - $340K/yr

This is a high-impact, full-cycle role focused on $400K+ enterprise deals. You will operate at ... Additionally, Actively AI leverages current market data to determine compensation, so posted ...

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Data 400K information

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$44.5K

$129.7K

$177.5K

How much do data 400k jobs pay per year?

As of Jun 4, 2026, the average yearly pay for data 400k in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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 background in mathematics or computer science, often supported by a bachelor's degree in a related field. Familiarity with data analysis tools like SQL, Excel, Python, R, and data visualization platforms such as Tableau or Power BI is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and conveying insights to stakeholders. These skills ensure accurate data-driven decision making that can drive business performance and innovation.

What are some common challenges faced by data analysts working with large-scale datasets, and how are these typically addressed in professional environments?

Data analysts working with large-scale datasets often encounter challenges such as data quality issues, slow processing speeds, and difficulties in data integration from multiple sources. To address these, organizations typically invest in robust data infrastructure, such as distributed computing platforms and cloud-based tools, to handle large volumes of data efficiently. Analysts are also encouraged to develop strong data cleaning and transformation skills, and to collaborate closely with data engineers and IT teams to ensure data pipelines run smoothly. Regular training and cross-functional meetings help keep everyone aligned on best practices for managing big data.

What are Data 400K jobs?

Data 400K jobs typically refer to high-level data-related roles, such as data scientists, data engineers, or chief data officers, that offer annual salaries around $400,000 or more. These positions usually require advanced expertise in data analysis, machine learning, big data technologies, and significant experience in the field. Professionals in these roles often lead data strategy, oversee large teams, and drive critical business decisions using data. They are most commonly found in industries like finance, tech, and consulting where data-driven decision-making is crucial.

What is the difference between Data 400K vs Data Analyst?

AspectData 400KData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related field; certifications like Microsoft Data AnalystBachelor's in related field; certifications like Microsoft Data Analyst or SQL certifications
Work EnvironmentData centers, analytics firms, large corporationsBusiness offices, consulting firms, tech companies
Industry UsageData engineering, analytics, big data projectsBusiness intelligence, reporting, data interpretation

Data 400K typically refers to a specialized data engineering or big data role involving large-scale data processing, while Data Analyst focuses on interpreting data to inform business decisions. Both roles require similar educational backgrounds and certifications, but Data 400K often involves working with more complex data infrastructure and tools. Understanding these differences helps job seekers target the right roles based on their skills and career goals.

Infographic showing various Data 400K job openings in the United States as of May 2026, with employment types broken down into 79% Part Time, and 21% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Data Scientist

Data Scientist

Triumph

San Francisco, CA • On-site

$200K - $400K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 3 days ago

Job description

The Role

As a Data Scientist, you'll own the quantitative systems that drive how millions of real-money players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.

You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches real money and real users. You see the impact in the numbers the next day.

What You'll Do

  • Monetization & Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.

  • User Journey & Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.

  • Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.

  • Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.

  • Growth & Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.

  • Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.

Qualifications

  • Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.

  • True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.

  • Proficiency in Python and SQL.

  • Experience working with large-scale user or behavioral datasets.

Preferred Qualifications

  • Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.

  • Prior experience as a quantitative trader or quantitative researcher.

  • Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.

  • Nationally competitive in any activity. Some members of our team include national champions in debate, Clash Royale, and Poker.

Why Triumph?

  • High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.

  • High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.

  • High energy. Passionate team who are proud of our work and velocity (16x year over year growth).

  • Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.

Our team gathers 5 days a week at Triumph’s headquarters at Levi’s Plaza in San Francisco.

Compensation Range: $200K - $400K