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Data Science Project Jobs (NOW HIRING)

InteliX Systems

Data Scientist

Washington, DC · On-site

They should be able to explain how data science project works, what data science they have done. In-depth knowledge on how systems work, star schemas, how reporting works, etc. Responsible for ...

Samprasoft

10478- Data Scientist

Washington, DC · On-site

They should be able to explain how data science project works, what data science they have done. In depth knowledge on how systems works, star schemas, how reporting works, etc. Responsible for ...

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How much do data science project jobs pay per hour?

As of Jun 3, 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 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 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 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 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.

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 job categories do people searching Data Science Project jobs look for? The top searched job categories for Data Science Project jobs are:
Data Science Project jobs near you
Infographic showing various Data Science Project job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $119,617 per year, or $57.5 per hour.
SME III Data Scientist

SME III Data Scientist

Koniag Government Services

Arlington, VA • On-site

Full-time

Posted 18 days ago

Job description

Job Summary:
Koniag Government Services is seeking a SME III Data Scientist to support KMS and their government customer at the Pentagon. The role requires expertise in data science programming, machine learning model development, and managing the data science project lifecycle.
Responsibilities:
• Fifteen (15) years’ experience as a data scientist.
• Fifteen (15) years’ experience with expert-level proficiency in data science programming languages such as Python and/or Strong experience with data querying languages (e.g., Structured Query Language (SQL)) and working with large-scale datasets.
• Fifteen (15) years’ experience with extensive theoretical knowledge and practical experience in developing and deploying machine learning models.
• Demonstrated specific, hands-on experience with Large Language Models (LLMs) is required.
• Fifteen (15) years’ experience with a mastery of statistical methods, including hypothesis testing, regression, classification, and clustering techniques.
• Ten (10) years’ experience using data visualization libraries and platforms (e.g., Matplotlib, Seaborn, Plotly, Tableau) to create impactful reports and dashboards.
• Ten (10) years’ experience managing the entire data science project lifecycle: from problem definition and data collection to model deployment and communication of findings.
Qualifications:
Required:
• Fifteen (15) years’ experience as a data scientist.
• Fifteen (15) years’ experience with expert-level proficiency in data science programming languages such as Python and/or Strong experience with data querying languages (e.g., Structured Query Language (SQL)) and working with large-scale datasets.
• Fifteen (15) years’ experience with extensive theoretical knowledge and practical experience in developing and deploying machine learning models.
• Demonstrated specific, hands-on experience with Large Language Models (LLMs) is required.
• Fifteen (15) years’ experience with a mastery of statistical methods, including hypothesis testing, regression, classification, and clustering techniques.
• Ten (10) years’ experience using data visualization libraries and platforms (e.g., Matplotlib, Seaborn, Plotly, Tableau) to create impactful reports and dashboards.
• Ten (10) years’ experience managing the entire data science project lifecycle: from problem definition and data collection to model deployment and communication of findings.
• Master’s degree from an accredited college or university in engineering or science discipline relevant to the field of data science.
• TS/SCI (SAP eligible)
Preferred:
• Military or OSW experience
Company:
Koniag Government Services is a Professional Services and Operational Management to Federal Government. Founded in 1971, the company is headquartered in Chantilly, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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