Python Developer | $77/hr Remote

Python Developer | $77/hr Remote

Posted Today by Crossing Hurdles

Negotiable
Undetermined
Remote
United Kingdom

Summary: The role of Data Scientist (Kaggle Grandmaster) involves analyzing complex datasets to derive insights and inform modeling strategies. The position requires building predictive models and collaborating with machine learning engineers to ensure reliable data workflows. Candidates must demonstrate excellence in Kaggle competitions and possess strong analytical and communication skills. This is a flexible hourly contract position with a commitment of 30–40 hours per week, primarily remote.

Key Responsibilities:

  • Analyze large, complex datasets to uncover patterns, generate insights, and inform modeling strategies.
  • Build end-to-end predictive models, statistical analyses, and machine learning pipelines across various datasets.
  • Design and implement robust validation strategies, experimentation frameworks, and analytical methodologies.
  • Develop automated data workflows, feature engineering pipelines, and reproducible research environments.
  • Conduct exploratory data analysis, hypothesis testing, and model-driven investigations to support research and product teams.
  • Translate analytical and modeling outcomes into clear, actionable recommendations for stakeholders.
  • Collaborate with machine learning engineers to productionize models and ensure reliable data workflows.
  • Create structured dashboards, reports, and documentation to communicate findings.
  • Support high-impact research and product initiatives through advanced analytical problem-solving.

Key Skills:

  • Kaggle Competitions Grandmaster or equivalent demonstrated excellence.
  • Strong professional experience in data science or applied analytics.
  • Strong proficiency in Python and data science libraries such as Pandas, NumPy, Polars, and scikit-learn.
  • Hands-on experience building machine learning models end-to-end.
  • Solid understanding of statistical methods, experiment design, and causal analysis.
  • Experience with modern data stacks, including SQL and distributed datasets.
  • Excellent communication skills for presenting complex analytical insights.
  • Ability to work independently in a remote, fast-paced environment.
  • Strong analytical thinking and problem-solving skills with attention to detail.

Salary (Rate): £77.00/hr

City: undetermined

Country: United Kingdom

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Position: Data Scientist (Kaggle Grandmaster)
Type: Hourly Contract (Independent Contractor)
Compensation: $56 – $77/hour
Location: Remote
Commitment: 30–40 hours/week (flexible; full-time optional)

Role Responsibilities

  • Analyze large, complex datasets to uncover patterns, generate insights, and inform modeling strategies.
  • Build end-to-end predictive models, statistical analyses, and machine learning pipelines across tabular, time-series, NLP, and multimodal datasets.
  • Design and implement robust validation strategies, experimentation frameworks, and analytical methodologies.
  • Develop automated data workflows, feature engineering pipelines, and reproducible research environments.
  • Conduct exploratory data analysis, hypothesis testing, and model-driven investigations to support research and product teams.
  • Translate analytical and modeling outcomes into clear, actionable recommendations for engineering, product, and leadership stakeholders.
  • Collaborate with machine learning engineers to productionize models and ensure data workflows operate reliably at scale.
  • Create structured dashboards, reports, and documentation to clearly communicate findings.
  • Support high-impact research and product initiatives through advanced analytical problem-solving.

Requirements

  • Kaggle Competitions Grandmaster or equivalent demonstrated excellence (top-tier rankings, multiple medals, or exceptional competition performance).
  • Strong professional experience in data science or applied analytics.
  • Strong proficiency in Python and data science libraries such as Pandas, NumPy, Polars, and scikit-learn.
  • Hands-on experience building machine learning models end-to-end, including feature engineering, training, evaluation, and deployment.
  • Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis.
  • Experience working with modern data stacks, including SQL, distributed datasets, dashboards, and experiment tracking tools.
  • Excellent communication skills with the ability to clearly present complex analytical insights.
  • Ability to work independently in a remote, fast-paced research environment.
  • Strong analytical thinking and problem-solving skills with attention to detail.

Application Process
Upload resume (Kaggle profile required)
Interview (15–30 min)
Submit form