Data Analyst | $56/hr Remote | Mercor

Crossing Hurdles
Sheffield
3 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst | FTC

Data Analyst

Data Engineer / Analyst

Data Analyst

Data Analyst - E-Commerce

Data Analyst

At Crossing Hurdles, we work as a referral partner. We refer candidates to Mercor that collaborates with the world’s leading AI research labs to build and train cutting-edge AI models.


Organization: Mercor

Position: Data Scientist (Kaggle Grandmaster)

Referral Partner: Crossing Hurdles

Type: Hourly Contract

Compensation: $56/hour

Location: Remote

Commitment: 10–40 hours/week


Role Responsibilities (Training support will be provided)

  • Analyze large, complex datasets to identify patterns and generate actionable insights.
  • Build high-performing predictive models, statistical analyses, and ML pipelines across varied data types.
  • Design and implement rigorous experiment frameworks and validation strategies.
  • Automate workflows, feature pipelines, and reproducible research environments.
  • Conduct exploratory data analysis, hypothesis testing, and interpret modeling outcomes.
  • Collaborate with ML engineers and research teams to productionize models at scale.
  • Present findings through clear documentation, dashboards, and reports.


Requirements

  • Kaggle Competitions Grandmaster or equivalent achievement (multiple medals or top-tier rankings).
  • Strong experience in data science, analytics, or ML-driven research.
  • Proficiency in Python and key libraries such as Pandas, NumPy, Polars, and scikit-learn.
  • Solid knowledge of experiment design, causal inference, and statistical modeling.
  • Familiarity with SQL, distributed data systems, and experiment tracking tools.
  • Excellent communication and data storytelling skills.


Application Process (Takes 20 min)

  1. Upload resume
  2. AI interview based on your resume (15 min)
  3. Submit form

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.