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Data Science Project Jobs (NOW HIRING)

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

Project Manager, AI and Data Science

Houston, TX · Hybrid

$49.50 - $66.75/hr

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

Project Manager, AI and Data Science

Pipersville, PA · Hybrid

$52.75 - $71.25/hr

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

Project Manager, AI and Data Science

Pipersville, PA · Hybrid

$52.75 - $71.25/hr

We are hiring a Project Manager, AI & Data Science, who will act as both Scrum Master for the Data Science team and Project Manager for SaaS AI products such as ChatGPT Enterprise, Veo 3, Slack AI ...

Lead end-to-end data science projects using agile and iterative approaches. * Develop and deploy AI/ML models, including propensity modeling. * Drive data engineering requirements to support model ...

Additionally, you will coordinate data science projects, collaborate with partners across University Data and Analytics (UDA), and provide day-to-day leadership and supervision of the Data Science ...

Own end‑to‑end delivery of high‑impact data science projects -- from ambiguous business request to production‑ready system. * Design and maintain data pipelines, data models, and governance ...

Associate Director of Data Science

Columbia, MD · On-site

$58K - $59K/yr

Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data scientists. * Design and implement AI solutions leveraging advanced techniques, including prompt ...

Associate Director of Data Science

Columbia, MD · On-site +1

$58K - $59K/yr

Lead the delivery of AI and data science projects, managing a team of 4-5 developers and data scientists. * Design and implement AI solutions leveraging advanced techniques, including prompt ...

Showing results 21-40

Data Science Project information

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$16

$57

$80

How much do data science project jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for data science project in the United States is $57.51, according to ZipRecruiter salary data. Most workers in this role earn between $49.76 and $67.31 per hour, depending on experience, location, and employer.

What is a data science project?

A Data Science Project is a structured process in which data scientists use statistical, analytical, and machine learning techniques to extract insights or solve problems using data. Such projects typically involve steps like data collection, data cleaning, exploratory data analysis, modeling, and communicating results. The goal can range from predicting trends and automating tasks to uncovering hidden patterns in data. Successful data science projects often require collaboration between domain experts, data engineers, and analysts to ensure the solutions are practical and actionable.

What are some common challenges faced when managing a data science project, and how can they be addressed?

Managing a data science project often involves challenges such as unclear project objectives, data quality issues, and aligning technical work with business goals. Communication between data scientists, stakeholders, and IT teams is crucial to ensure everyone is on the same page regarding expectations and deliverables. Establishing clear project milestones, maintaining thorough documentation, and validating data sources early in the process can help mitigate these issues. Regular check-ins and agile practices also support adaptability as project requirements evolve.

What are the key skills and qualifications needed to thrive in data science project roles, and why are they important?

To thrive in Data Science Project roles, you need a solid background in statistics, programming (often Python or R), and knowledge of data modeling, typically supported by a relevant degree or coursework. Familiarity with tools like Jupyter Notebooks, SQL, machine learning libraries (such as scikit-learn or TensorFlow), and sometimes cloud platforms is common. Strong problem-solving abilities, effective communication, and collaboration skills help translate complex findings into actionable business insights. These skills ensure data-driven projects are executed efficiently, results are understood by stakeholders, and organizational goals are met.

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

AspectData Science ProjectData Analyst
Required CredentialsTypically requires a degree in data science, statistics, or related fields; certifications like Certified Data Scientist are commonOften requires a degree in statistics, mathematics, or related fields; certifications like Microsoft Data Analyst Associate are common
Work EnvironmentProject-based, involving data collection, cleaning, modeling, and presentation; often in tech, finance, or healthcare industriesFocuses on data reporting, visualization, and insights generation; works across various industries
Employer & Industry UsageUsed in organizations aiming to develop predictive models and advanced analyticsUsed in organizations needing routine data reporting and business insights

In summary, a Data Science Project involves developing complex models and analytics, often requiring advanced skills and certifications, while a Data Analyst focuses on interpreting data and creating reports for business decision-making. Both roles are essential but differ in scope and technical depth.

What projects can I do for data science?

Data science projects can include analyzing datasets to uncover insights, building predictive models, developing data visualizations, or working on machine learning algorithms. These projects help demonstrate skills in programming, statistics, and tools like Python, R, or SQL, and are valuable for building a portfolio or gaining practical experience.
More about Data Science Project jobs

What are the most commonly searched types of Data Science Project jobs?

The most popular types of Data Science Project jobs are:

What are popular job titles related to Data Science Project jobs?

For Data Science Project jobs, the most frequently searched job titles are:

Infographic showing various Data Science Project job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $119,617 per year, or $57.5 per hour.

Lead Data Scientist

Houston, TX • Remote

Full-time

Posted 13 days ago


Key responsibilities

  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.

  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.

  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.


Job description

Lead Data Scientist

United States | Remote within GA, LA, OK, TN or TX | Direct Hire

The Opportunity

A large healthcare organization is seeking an experienced Lead Data Scientist to lead advanced analytics initiatives involving complex structured and unstructured data.

This role combines hands-on data science, statistical modeling, machine learning, stakeholder engagement, and technical leadership. The successful candidate will partner with cross-functional teams to translate complex business challenges into analytical solutions and deliver actionable insights that support data-driven decision-making.

The position reports to the Manager of Data Science and includes responsibility for leading high-priority projects, mentoring other data scientists, and presenting analytical findings to senior leadership.

Key Responsibilities
  • Lead high-priority data science and advanced analytics initiatives with organization-wide impact.
  • Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.
  • Develop custom data models and algorithms to address business questions and improve operational performance.
  • Build and apply predictive models and analytical approaches to key business metrics.
  • Conduct research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
  • Develop and test hypotheses and translate findings into clear, actionable recommendations.
  • Maintain existing analytical models and evaluate model performance and goodness of fit.
  • Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.
  • Identify, investigate, and resolve complex data quality and data availability issues.
  • Improve the efficiency, scalability, and reliability of data processes.
  • Manage multiple small and medium-sized analytical engagements and competing priorities.
  • Provide technical guidance, coaching, and mentoring to other data scientists.
  • Help educate broader audiences on data science capabilities, techniques, and developments.
  • Communicate complex analytical concepts to both technical and non-technical stakeholders.
  • Present analytical findings and recommendations to senior leadership.
  • Assist in evaluating data science tools, platforms, and vendors.
Required Qualifications
  • Bachelor's Degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another related STEM discipline.
  • Minimum of 7 years of professional Data Science experience.
  • Strong business analytical capabilities, including process analysis, modeling, spreadsheets, procedures, and analytical problem-solving.
  • Strong understanding of data architecture and design principles.
  • Advanced analytical reasoning, problem-solving, and decision-making skills.
  • Demonstrated ability to independently investigate complex problems and identify the information necessary to reach sound conclusions.
  • Ability to manage multiple initiatives with competing priorities while meeting project goals and deadlines.
  • Excellent written and verbal communication skills.
  • Ability to explain complex technical and analytical information to both technical and business audiences.
  • Strong stakeholder management and client-facing capabilities.
  • Ability to work independently with minimal supervision in a fast-paced, multidisciplinary environment.
  • Strong ability to troubleshoot issues, recommend solutions, and manage challenging stakeholder situations.
Required Technical & Analytical Experience

Candidates should demonstrate strong practical knowledge of:

  • Machine learning techniques, including:
    • Clustering
    • Decision tree learning
    • Artificial neural networks
    • Understanding of the practical advantages and limitations of different modeling approaches
  • Advanced statistical techniques and concepts, including:
    • Regression
    • Statistical distributions
    • Statistical testing
    • Time series forecasting
    • A/B testing
    • Clustering
  • Predictive modeling and advanced analytics.
  • Data mining, visualization, and pattern analysis.
  • Advanced SQL and database management tools.
  • Programming for analytical and data science applications.
  • Statistical analysis tools.
  • The full data science project lifecycle.
  • Analysis of large, complex, and incomplete data sources.
  • Model evaluation and interpretation of analytical results.
Leadership & Stakeholder Management

The ideal candidate will be able to combine technical depth with strong business communication.

The role requires the ability to:

  • Translate complex data into meaningful business insights.
  • Gather requirements directly from stakeholders.
  • Build compelling, evidence-based data stories.
  • Present findings confidently to senior and executive leadership.
  • Lead cross-functional analytical initiatives.
  • Mentor and provide technical guidance to less experienced data science professionals.
  • Translate complex findings into clear recommendations for a broad range of stakeholders.
Preferred Experience

The following experience is preferred but not required:

  • Master's Degree in Data Science.
  • Professional experience within a hospital or healthcare environment.
  • Medical informatics.
  • Healthcare information technology.
  • Healthcare finance or revenue cycle data management.
  • Electronic Health Record (EHR) data management.
Candidate Profile

The strongest candidate will combine advanced quantitative expertise with strong business judgment and communication skills.

They should be comfortable moving from raw and incomplete data through statistical analysis and modeling, identifying meaningful insights, and ultimately presenting those findings in a concise and actionable manner to senior stakeholders.

A strong analytical mindset, executive-level communication capability, project ownership, and the ability to mentor others are important for success in this position.

Work Arrangement

This opportunity is remote, but candidates must be able to work from one of the following states:

  • Georgia
  • Louisiana
  • Oklahoma
  • Tennessee
  • Texas

Travel of up to 20% may be required.

Work Authorization

Some visa sponsorship arrangements may be supported for this opportunity. Eligibility should be evaluated based on the individual candidate's circumstances.