Synthires
Senior Machine Learning & Data Scientist (Remote | $120–$170/hr)

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Senior Machine Learning & Data Scientist
Position: Senior Machine Learning & Data Scientist
Type: Hourly Contract (Part-Time)
Compensation: $120–$170/hour
Location: Remote
About the Opportunity
This opportunity is for experienced Senior Machine Learning & Data Scientists interested in contributing 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 machine learning models, data science solutions, statistical analyses, and predictive approaches. You'll apply your expertise across machine learning, data science, statistical modeling, and advanced analytics to assess AI outputs and provide technical feedback that improves model performance.
No prior AI experience is required. Your machine learning and data science expertise are the primary qualifications for success in this role.
Responsibilities
- Evaluate AI-generated machine learning models, data analyses, and statistical solutions for accuracy and technical quality.
- Solve complex machine learning, statistical modeling, predictive analytics, and data science problems.
- Review AI-generated approaches involving data preprocessing, feature engineering, model development, training, validation, and evaluation.
- Analyze large datasets, predictive models, algorithms, and statistical methodologies to identify errors and inconsistencies.
- Evaluate model performance, experimentation results, and analytical methodologies using appropriate statistical and machine learning techniques.
- Compare multiple AI-generated solutions and assess their technical strengths, weaknesses, and reasoning quality.
- Provide structured technical feedback to improve AI accuracy, machine learning reasoning, and analytical capabilities.
- 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 experience in Machine Learning, Data Science, or a related quantitative field.
- Strong expertise in machine learning, statistical analysis, predictive modeling, and data analytics.
- Proficiency in Python and SQL, with experience using modern data science and machine learning libraries.
- Strong understanding of machine learning algorithms, probability, statistics, model evaluation, and experimental design.
- Experience developing, evaluating, or deploying machine learning models and data science solutions.
- Ability to assess 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 PyTorch, TensorFlow, scikit-learn, XGBoost, or similar machine learning frameworks.
- Experience working with LLMs, generative AI, AI agents, or AI model evaluation.
- Experience with deep learning, natural language processing, computer vision, or recommender systems.
- Familiarity with MLOps, cloud platforms, distributed computing, Docker, or production machine learning systems.
- Experience with A/B testing, causal inference, time-series analysis, experimentation, or advanced statistical methods.
- Prior experience with AI evaluation, technical review, data annotation, 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.”
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