data science professionals

MAG LLC
New York, NY, United States
2 days ago

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$239,200.0 - $343,200.0
Working hours
Regular working hours

Tech stack

A/B Testing Artificial Intelligence Data Analysis Data Cleansing Data Files Decision Support Systems Executive Information Systems Python (Programming Language) Machine Learning SQL Databases Usage Analysis Scripting
+5 more
Model Validation Stripe Information Technology Data Analytics Marketplace

Job description

We are sharing a specialised part-time consulting opportunity for experienced data science professionals skilled in experiment design, A/B testing, product analytics, metric development, SQL and Python analysis, dashboard review, and structured evaluation of real-world data science work.

This role supports current and upcoming remote consulting opportunities focused on evaluating professional data science deliverables and defining clear standards for high-quality analytical work. Selected professionals will develop task-specific assessment criteria, review AI-generated and human-created outputs, score completed work, and provide detailed written feedback grounded in practical industry experience.

Key Responsibilities

Data Science Deliverable Evaluation

  • Review analytical studies, predictive models, dashboards, experiment readouts, and written recommendations
  • Assess work for technical accuracy, methodological quality, business relevance, and clarity
  • Identify analytical errors, unsupported conclusions, weak assumptions, and inappropriate methodological choices
  • Determine whether deliverables meet professional standards for product, growth, and business decision-making

Evaluation Criteria & Rubric Development

  • Design precise, task-specific grading criteria for real-world data science deliverables
  • Define measurable standards covering analytical approach, statistical validity, metric selection, interpretation, and communication
  • Ensure evaluation frameworks reflect realistic expectations from industry data science teams
  • Refine assessment criteria based on structured feedback and calibration outcomes

Experimentation & Product Analytics Review

  • Evaluate experiment design, A/B testing methodology, sample construction, statistical analysis, and result interpretation
  • Review product, growth, and operational metrics for relevance, consistency, and decision-making value
  • Assess whether findings are supported by appropriate evidence and analytical methods
  • Identify risks involving bias, confounding variables, metric selection, or overinterpretation

SQL, Python & Analytical Review

  • Review SQL and Python-based analyses for correctness, efficiency, reproducibility, and clarity
  • Assess data preparation, transformation, validation, and modelling workflows
  • Evaluate dashboards and reporting outputs for accuracy, usability, and alignment with business questions
  • Review written recommendations for logical consistency and practical relevance

Scoring & Written Justification

  • Score AI-generated and human-created work against structured evaluation criteria
  • Provide detailed written explanations supporting each assessment decision
  • Apply consistent, evidence-based judgment across different datasets, industries, and analytical scenarios
  • Incorporate feedback from senior reviewers and adjust evaluation approaches efficiently, * Define what strong analytical reasoning and industry-quality execution should look like
  • Review realistic analyses, experiments, models, dashboards, and recommendations
  • Use your expertise to improve consistency, accuracy, and rigor across data science evaluation workflows
  • Participate in flexible assignments with competitive hourly compensation

Contract Details

  • Independent contractor role
  • Fully remote with flexible scheduling
  • Part-time workload depending on project availability and scope
  • Competitive rates between $115-$165 per hour depending on experience, technical depth, and project requirements
  • Weekly payments via Stripe or Wise
  • The selection process may include a resume review, brief technical assessment, or request for additional professional information
  • Projects may be extended, shortened, or adjusted depending on scope and performance
  • Work will not involve access to confidential or proprietary information from any employer, client, or institution

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

Requirements

  • At least 5 years of professional data science experience in an industry environment
  • Experience in product, growth, business operations, marketplace, or commercial data science
  • Strong command of experiment design, A/B testing, metric development, and statistical analysis
  • Advanced practical experience with SQL and Python
  • Ability to evaluate models, dashboards, analytical outputs, and written recommendations
  • Experience communicating findings to executive, product, operational, or commercial stakeholders
  • Exceptional written communication and the ability to explain technical judgments clearly
  • Strong attention to detail and comfort having evaluation decisions reviewed and calibrated

Educational Background

  • A degree in data science, statistics, computer science, mathematics, economics, engineering, or a related quantitative field is helpful
  • Graduate-level training in statistics, econometrics, machine learning, operations research, or a related discipline may be valuable
  • Professional experience in product analytics, experimentation, growth analytics, or business intelligence is highly relevant
  • Equivalent hands-on experience delivering complex analytical work in industry may also be considered

Nice to Have

  • Experience at a leading technology company, digital platform, marketplace, or data-driven consumer business
  • Familiarity with causal inference, experimentation platforms, forecasting, or predictive modelling
  • Experience developing executive dashboards, metric frameworks, and decision-support materials
  • Strong understanding of product funnels, retention, engagement, conversion, and growth metrics
  • Experience reviewing work produced by analysts, data scientists, or cross-functional technical teams
  • Previous involvement in AI evaluation, structured review, benchmarking, or quality-assurance projects
  • Experience developing analytical standards, training materials, or internal review frameworks, A/B Testing, Analysis Skills, Artificial Intelligence (AI), Benchmarking, Business Growth, Business Intelligence, Business Operations, Calibration, Communication Skills, Computer Science, Construction, Consulting, Cross-Functional, Data Analysis, Data Science, Data Sets, Decision Support, Design Evaluation, Detail Oriented, Econometrics, Economics, Experiment Design, Forecasting, Machine Learning, Mathematics, Metrics, Model Validation, Operations Research, Predictive Modeling, Product Reviews, Product Testing, Project Evaluation, Python Programming/Scripting Language, Quality Assurance, Quality Assurance Methodology, Quality Metrics, Reporting Dashboards, Request for Information (RFI), Risk Analysis, SQL (Structured Query Language), Standards Development, Statistics, Technical Analysis, Technical Consulting, Technical Presentation, Test Plan/Schedule, Usability Engineering, Workflow Analysis, Writing Skills

Apply for this position

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