Senior Data Scientist
Turing • Remote, Europe, United States
Education
PhD
Type
Hourly
Listed
186d ago
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From the Turing listing
About the Role
Exciting opportunity to work directly with researchers at a top 8 Frontier Lab. In this role you will design challenging real-world problems in data science, ML, and coding to test and improve state of the art LLMs. You will be part of a peer group of top STEM & ML Phds as a part of the program. You will be responsible for ensuring that human data generation (on agentic workflows) meets the highest standards of accuracy, nuance, and utility for model training.
Responsibilities
- Agentic Oversight: Design and implement frameworks to guide, monitor, and validate the data outputs generated by agentic taskers to ensure they align with gold-standard benchmarks.
- Methodology Development: Develop new methodologies to improve the performance of models through superior training data, including innovative approaches to data collection and insight generation.
- AI Integration: Utilize AI models and tools as integral components for evaluate synthesizing, and understanding complex datasets to drive data quality.
- Cross-Functional Partnership: Act as a critical technical partner, collaborating closely with Research, Engineering, and Product teams to define data excellence across the organization.
- Outcome Ownership: Solve ambiguous problems and influence stakeholders to ensure data intelligence outcomes directly support product and business objectives.
Required Qualifications
- Advanced Academic Background: PhD degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related domain.
- Extensive Analytical Experience: 10 years of experience using analytics to solve complex product or business problems, including querying databases and performing advanced statistical analysis.
- Technical Proficiency: Mastery of coding languages such as Python, R, or SQL for data manipulation, modeling, and automation.
Offer Details
- Rate: ~ $100-150/hour.
- Commitment: Minimum 30 hours per week (on week days).
- Employment Type: Contractor (no medical/paid leave).
- Duration: 3 months (expected start date: next week).
- Locations: North America, Europe.
Requirements
- Advanced Academic Background: PhD degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related domain.
- Extensive Analytical Experience: 10 years of experience using analytics to solve complex product or business problems, including querying databases and performing advanced statistical analysis.
- Technical Proficiency: Mastery of coding languages such as Python, R, or SQL for data manipulation, modeling, and automation.
- Must be eligible to work in one of: Remote, Europe
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
Sample questions for a Data Scientist role, written in-house to help you prepare.
How do you determine the required sample size for an experiment before running it?
I run a power analysis based on the minimum effect size that would actually matter for the business decision, the expected baseline variance, and the desired statistical power, typically 80%. Skipping this step is how teams end up running underpowered experiments that can't reliably detect real effects, then wrongly concluding a change had no impact.
What's the difference between correlation and causation, and how do you establish the latter with observational data?
Correlation just means two variables move together, which can be driven by a third confounding factor rather than either variable causing the other. With observational data, I look for natural experiments, instrumental variables, or matching techniques to approximate a controlled comparison, since a true randomized experiment usually isn't available and correlation alone can't support a causal claim.
How would you choose between a simpler statistical model and machine learning approach for a forecasting problem?
For data with clear seasonal and trend patterns and limited history, a statistical model like ARIMA or exponential smoothing is often more reliable than machine learning, which typically needs more data to outperform simpler methods. I'd benchmark both against a holdout period rather than assuming the more complex option is automatically better.
How do you handle a situation where your model's predictions need to be explained to justify individual decisions?
I'd use an inherently interpretable model where possible, or apply a post-hoc explanation method like SHAP values on top of a more complex model if the added performance is worth the extra explanation layer. The explanation needs to be accurate to how the model actually makes decisions, not just a plausible-sounding story layered on afterward.
Why this role
This Senior Data Scientist role designs challenging real-world data science, ML, and coding problems for a top-8 frontier AI lab, working alongside a peer group of STEM and ML PhDs. The work centers on agentic oversight, building frameworks that guide and validate the quality of human-generated training data.
Talent pool
We're light on Data Science candidates
We've matched 9 people with a Data Science background against 293 Data Science listings we've tracked, so most go out without one. Set up a profile and we'll consider you for a role like this one.
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Common questions
Do I need to be a software engineer to work for Turing?
No, not anymore. Turing built its name matching senior engineers with Silicon Valley companies, but it has since expanded into AGI infrastructure work and now hires non-engineering domain experts, technical writers, and researchers for post-training data annotation and RLHF. A strong analytical background and excellent English matter more than coding ability.
How does Turing's talent matching work?
Turing calls it the Intelligent Talent Cloud. You build a profile and go through vetting (automated tests, an AI-powered interview, practical skill assessments), and once vetted, Turing's algorithm surfaces your profile directly to partner companies like Fortune 500s and top AI labs. You don't browse listings or bid on work; matches come to you.
What does asynchronous AI training work mean in practice?
No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.
What does Data Science work look like for a Senior Data Scientist?
Tasks here are scoped to Data Science, not generic labeling. As a Senior Data Scientist, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Data Science) rather than following a one-size-fits-all rubric. If you don't have hands-on Data Science background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Expert is named directly in the listing. If you don't have hands-on experience with this, expect the screening process to test for it directly rather than accepting adjacent experience as a substitute.
How much does this specific role pay?
The listing doesn't state a rate. The $30–$65/hr shown here is our estimate from the role type and location (see /pay-methodology), so treat it as a rough guide and confirm the actual rate with the platform before committing time.
What happens when I click Apply on this listing?
You'll be taken to Turing's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Is a PhD required?
For this specific role, yes, or near-equivalent professional depth. The credential gate is enforced at the assessment stage, not just on paper. That said, active PhD candidates and people with equivalent published research have qualified without a formal degree. The assessment is the real filter.
Can I apply from outside Europe or the United States?
This specific role is open only to people based in Europe and the United States. If you are somewhere else, applying is unlikely to lead to an offer even if you pass the assessment, because the restriction is usually about where the work can legally be contracted rather than your skills. Read the full description for any tax-residency or right-to-work caveats before you apply, since they can differ by country.