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Data Science Analytics Jobs (NOW HIRING)

Zeta Global

Senior Manager, Data Science & Analytics

$125K - $145K/yr

THE ROLE Zeta Global is looking for a seasoned, external client-engaging Senior Manager, Data Science & Analytics (individual contributor role) for its ZX Activation division. They will be ...

Discord

Data Scientist, Analytics

San Francisco, CA · On-site

$160K - $180K/yr

As a member of the Data Science & Analytics team, you will help Discord achieve its mission of making it easier and more fun for people to talk and hang out before, during, and after playing games.

Maayee Inc

Analytics Lead / Data Scientist

Suwanee, GA · On-site

Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Analytics, or related field. 5+ years of experience in analytics, data science, or business intelligence. Strong skills ...

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Data Science Analytics information

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$24

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$94

How much do data science analytics jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for data science analytics in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Science Analytics professional, and why are they important?

To thrive in Data Science Analytics, a strong background in statistics, data modeling, and programming (often with a degree in computer science, mathematics, or a related field) is essential. Familiarity with tools such as Python, R, SQL, and data visualization platforms like Tableau or Power BI, as well as knowledge of machine learning libraries, is typically required. Critical thinking, problem-solving, and effective communication skills help professionals translate complex data insights into actionable business strategies. These competencies are crucial for extracting meaningful information from data and driving informed decision-making within organizations.

Is AI replacing data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, allowing analysts to focus on more complex insights and strategic decision-making. While AI tools can augment their work, human expertise remains essential for interpreting results, understanding context, and making nuanced judgments. Data analysts with skills in machine learning, programming, and data visualization are increasingly valuable in this evolving environment.

How do data science analytics professionals typically collaborate with other departments within an organization?

Data science analytics professionals often work closely with teams across the organization, such as marketing, finance, product development, and IT. Their role involves understanding business needs, gathering requirements, and translating complex data findings into actionable insights for non-technical stakeholders. Effective communication and teamwork are essential, as data scientists may participate in cross-functional meetings, present their analyses, and tailor their recommendations to support strategic decision-making. This collaborative approach not only enhances the impact of analytics projects but also fosters continuous learning and innovation within the organization.

What is the difference between Data Science Analytics vs Data Analyst?

AspectData Science AnalyticsData Analyst
Required CredentialsDegree in Data Science, Statistics, or related fields; programming skillsDegree in Statistics, Mathematics, or related fields; proficiency in Excel and SQL
Work EnvironmentOften involves complex modeling, machine learning, and predictive analyticsFocuses on data cleaning, reporting, and visualization
Employer & Industry UsageTech companies, finance, healthcare, and research institutionsBusiness, marketing, finance, and operations across various industries

Data Science Analytics and Data Analysts both work with data, but Data Science Analytics typically involves advanced modeling and predictive techniques, while Data Analysts focus on data reporting and visualization. The roles often overlap, but Data Science Analytics requires more technical skills and a deeper understanding of algorithms.

What is the job of data science and analytics?

Data science and analytics involve collecting, processing, and analyzing large datasets to extract meaningful insights that support decision-making. Professionals in this field use statistical methods, programming tools like Python or R, and visualization techniques to identify trends, solve problems, and improve business outcomes.

What is data science analytics?

Data science analytics is the process of extracting insights and knowledge from data using statistical, mathematical, and computational techniques. It involves collecting, cleaning, analyzing, and visualizing data to help organizations make informed decisions. Professionals in this field use tools like Python, R, and SQL to interpret complex data sets, build predictive models, and identify trends or patterns. Data science analytics plays a key role in industries such as finance, healthcare, retail, and technology, enabling businesses to optimize operations and improve outcomes.

Is 40 too late for data science?

Data science analysts and professionals can enter the field at any age, including 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and tools like Python or R, as well as gaining experience through projects or certifications. Age is less important than skills, continuous learning, and adapting to industry changes.

What jobs can you get with data science and analytics?

Data science and analytics skills open opportunities for roles such as data analyst, data scientist, business intelligence analyst, machine learning engineer, and data engineer. These positions typically require proficiency in programming languages like Python or R, statistical analysis, and data visualization tools, often within technology, finance, healthcare, or marketing industries.
More about Data Science Analytics jobs
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What states have the most Data Science Analytics jobs? States with the most job openings for Data Science Analytics jobs include:
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Data Science Analytics jobs near you

Remote | Data Science & Analytics Workflow Consultant -- $75-$130/hour

24-MAG

New York, NY • Remote

$75 - $130/hr

Part-time

Posted 19 days ago

Job 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

Professionals in this role may contribute to:

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

Ideal Profile

Strong candidates may have:

  • 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

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.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy.