[Hiring] Data Science & Analytics Workflow Consultant @24-MAG

Role Description

We are sharing a specialised part-time consulting opportunity for professionals experienced in data science, analytics engineering, business intelligence, SQL analysis, experimentation, data engineering, and structured data workflow review. This role supports current and upcoming remote consulting opportunities focused on structured data science review, analytics workflow analysis, business intelligence assessment, experimentation review, data pipeline evaluation, metric documentation, and high-quality project execution. Selected professionals will apply their data and analytics expertise to review realistic technical scenarios, evaluate analytical requirements, prepare structured written outputs, and support accurate, evidence-based data workflow tasks.

Key Responsibilities

• Analytics, BI & Metric Review
  • Review data scenarios involving SQL analysis, ad-hoc business questions, dashboard specifications, metric definitions, funnel analysis, cohort analysis, and reporting outputs.
  • Evaluate analytical outputs against source data, defined business logic, expected numerical results, and documented requirements.
  • Support structured review of SQL queries, BI dashboards, dashboard specs, metric documentation, and analytical summaries.
  • Identify missing assumptions, query issues, metric inconsistencies, reporting gaps, and expected analysis outcomes.
• Experimentation & Data Science Support
  • Review experimentation scenarios involving A/B test design, readouts, lift calculations, statistical significance, guardrail metrics, and decision criteria.
  • Evaluate experiment outputs against defined metrics, expected values, testing assumptions, and analytical standards.
  • Support structured review of data science workflows, Python-based analyses, statistical outputs, and business interpretation materials.
  • Prepare clear written explanations for data science and analytics decisions based on source materials and verifiable criteria.
• Data Engineering & Pipeline Workflow Review
  • Review data engineering scenarios involving ETL/ELT pipelines, dbt models, data quality monitoring, warehouse schema design, Airflow or Dagster DAGs, and pipeline documentation.
  • Evaluate pipeline outputs, schemas, transformations, orchestration logic, and data quality checks against documented requirements.
  • Support structured review of data artifacts such as dbt models, schema diagrams, data contracts, test suites, DAGs, and warehouse documentation.
  • Maintain accuracy, consistency, and professional judgment across submitted work.

Qualifications

• 3+ years of experience as a data scientist, analytics engineer, BI analyst, data analyst, product analyst, data engineer, decision scientist, or related data professional.
• Working fluency in at least two areas such as advanced SQL, dbt, data warehousing, Snowflake, BigQuery, Redshift, experimentation, A/B testing, pipeline orchestration, metric modeling, or Python for analysis.
• Familiarity with tools such as SQL, Python, dbt, Airflow, Dagster, Snowflake, BigQuery, Redshift, Databricks, Looker, Tableau, Mode, Hex, Metabase, Power BI, or similar data and analytics systems.
• Comfort reading and preparing data artifacts such as SQL queries, dbt models, experiment readouts, dashboard specs, schema diagrams, metric definitions, and pipeline documentation.
• Strong written communication skills and ability to explain data decisions clearly.
• Ability to follow structured instructions and produce evidence-based work.

Educational Background

• A degree or professional background in data science, statistics, mathematics, computer science, economics, engineering, business analytics, information systems, or a related quantitative field is helpful.
• Equivalent practical experience in data science, analytics engineering, business intelligence, experimentation, data engineering, or data workflow review is also highly relevant.

Nice to Have

• Experience in product, consumer, SaaS, marketplace, fintech, e-commerce, or data-mature company environments.
• Familiarity with experimentation frameworks, metric governance, data quality monitoring, warehouse design, pipeline orchestration, or modern data stack workflows.
• Experience preparing or reviewing SQL queries, dbt models, experiment readouts, dashboards, schema diagrams, funnel analyses, cohort reports, or data documentation.
• Experience with Python-based analysis, statistical testing, data modeling, analytics engineering, or pipeline QA.
• Strong attention to detail in data-heavy, metric-heavy, and documentation-based technical environments.

Why This Opportunity

• Apply data science and analytics expertise to structured remote project work.
• Contribute to high-quality analytics review, experimentation assessment, BI documentation, and data pipeline workflow analysis.
• Work on flexible, project-based assignments aligned with your technical background.
• Use your data judgment in a focused, detail-oriented technical environment.
• Remote structure with competitive hourly compensation.

Contract Details

• Independent contractor role.
• Fully remote with flexible scheduling.
• Part-time commitment depending on project availability.
• Competitive rates between $75–$130 per hour depending on expertise.
• Weekly payments via Stripe or Wise.
• 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.