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Company Summary

Company Reviews

DataForce delivers high-quality, multimodal training data and services to power the next generation of AI. From large language models to voice, image, and video generation, DataForce supports AI innovators in tech, life sciences, automotive, and beyond with scalable, secure solutions for development, testing, and safety. Backed by cutting-edge technology and over one million data contributors, DataForce helps ensure AI systems are accurate, adaptable, and ready for real-world deployment.

DataForce is part of TransPerfect, the world’s largest provider of language and AI solutions for global business, with offices in more than 140 cities worldwide. Learn more at www.dataforce.ai.

Contact: [email protected]

Rating Reviews

Rating is calculated based on 5 reviews and is evolving.

Featured Reviews

Data Analyst
3.3
27 February 2026
Hybrid Model Is Decent, But Not Truly Flexible
Pros: They do offer a hybrid work model, which is nice. For us Data Analyst roles in the Seattle office, we're usually in three days a week. It's good to get some WFH time and avoid the daily commute.
Cons: The "flexibility" often means being online constantly, even on WFH days. It's tough to truly disconnect, and I've felt pressured to respond quickly. They also push for more in-office days if projects require it, making consistent hybrid work tricky.
Advice to Management: Truly commit to the hybrid model without making remote days feel like just another in-office day. Give teams more autonomy on office presence and trust them to get work done.
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Junior Data Scientist
3.1
28 February 2026
Growth is slow, good for entry-level experience
Pros: You get solid experience with SQL and basic data analytics tools, which is great if you're fresh out of school. There are always smaller machine learning projects to jump onto if you ask around. Being remote from Seattle is a huge plus for commute.
Cons: Career growth for data science roles feels pretty stagnant after the entry level. There's not much formal mentorship or clear paths to Senior Data Scientist. It's a mid-sized tech company, so things move slow, and promotion cycles are long.
Advice to Management: Invest more in formal career development plans and mentorship for data scientists. Create clearer pathways for junior roles to advance, especially for those interested in more advanced machine learning or data engineering tracks.
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Data Analyst
3.0
25 February 2026
Leadership Team Needs More Vision
Pros: The hybrid work model is pretty solid, offering good work flexibility in the Austin, TX office. I've gotten to work on some really interesting data analytics projects, which is great for building skills, especially for Data Analyst roles.
Cons: The leadership team often seems pretty disconnected from what we do daily. There's not a lot of clear direction from upper management, making it tough to see how my work fits into the bigger picture. It feels like they're just reacting instead of planning ahead.
Advice to Management: Try to be more present with the teams and communicate a clearer vision for where DataForce is headed. Empower team leads more to make decisions.
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Common Questions About DataForce

What is the day-to-day work environment like for a data analyst at DataForce, especially regarding collaboration?
What is DataForce's policy on remote or hybrid work for data analysts in the Dallas area?
What is the typical work environment like for a data analyst at DataForce, especially regarding team collaboration?
What is the typical team collaboration like for a Data Analyst role at DataForce, especially considering their focus on AI and machine learning projects?
What is the typical salary range for a Data Scientist role at DataForce, especially for someone with 3-5 years of experience in the San Francisco Bay Area?
What is the typical work environment like for a Data Analyst at DataForce, especially regarding collaboration and team dynamics?
What is the typical salary range for a Data Analyst role at DataForce, considering the company's presence in the tech industry?
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