Synthires
Senior Data Science Expert (Remote | $120–$170/hr)

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Senior Data Science Expert
Position: Senior Data Science Expert
Type: Hourly Contract (Part-Time)
Compensation: $120–$170/hour
Location: Remote
About the Opportunity
This opportunity is for experienced Senior Data Science Experts to contribute to advanced AI research and evaluation projects focused on improving the accuracy, reasoning, and analytical capabilities of next-generation AI systems.
The role involves evaluating AI-generated data science solutions, statistical analyses, predictive models, and machine learning outputs. You'll apply your expertise in data science, statistics, machine learning, predictive analytics, and advanced data analysis to assess AI outputs and provide expert feedback that improves model performance.
No prior AI experience is required. Your data science expertise, analytical reasoning, and professional experience are the primary qualifications for success in this role.
Responsibilities
- Evaluate AI-generated data science solutions, statistical analyses, and machine learning outputs for accuracy, quality, and technical soundness.
- Solve complex data analysis, statistical modeling, machine learning, and predictive analytics problems.
- Review AI-generated approaches involving data preprocessing, feature engineering, model development, validation, and evaluation.
- Analyze datasets, predictive models, algorithms, and statistical methodologies to identify errors, inconsistencies, and edge cases.
- Assess model performance, experimental results, and analytical methodologies using appropriate data science and statistical techniques.
- Compare multiple AI-generated solutions and evaluate their technical strengths, weaknesses, and reasoning quality.
- Provide structured expert feedback to improve AI accuracy, analytical reasoning, and model performance.
- Collaborate with technical reviewers and interdisciplinary teams to maintain consistent evaluation standards and data quality.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required Qualifications
- 3+ years of professional Data Science experience or equivalent industry/research experience.
- Strong expertise in data analysis, statistical modeling, machine learning, predictive modeling, and data visualization.
- Proficiency in Python and SQL, with experience using modern data science libraries and frameworks.
- Strong understanding of statistics, probability, machine learning algorithms, experimental design, and model evaluation.
- Experience developing, evaluating, or deploying data science and machine learning models.
- Ability to evaluate AI-generated technical solutions and identify methodological issues, errors, and edge cases.
- Excellent analytical, problem-solving, and written communication skills.


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Preferred Qualifications
- Experience with scikit-learn, PyTorch, TensorFlow, XGBoost, or similar machine learning frameworks.
- Experience working with large-scale datasets, advanced analytics, or production data science systems.
- Familiarity with AI, generative AI, LLMs, AI model evaluation, or data annotation.
- Experience with A/B testing, causal inference, time-series analysis, experimentation, or advanced statistical methods.
- Familiarity with cloud platforms, distributed computing, MLOps, or data engineering workflows.
- Prior experience with AI evaluation, technical review, or model quality assessment projects.
Compensation
- Competitive compensation of $120–$170/hour.
- Weekly payments.
- Independent contractor engagement.
Application Process
- Easy Apply on LinkedIn
- Check Email for Next Steps
- Participate in Resume Evaluation & Interview Stage
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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