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Data Science Analytics Jobs in Washington (NOW HIRING)

Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do: Our Data and Analytics consultants help clients maximize the value of their ...

Data Science Manager

Columbia, MD · On-site

$125K - $160K/yr

Key Responsibilities Data Science & Analytics * Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints. * Translate business ...

Data Science Consulting Travel Required: None Clearance Required: Active Top Secret SCI with Polygraph What You Will Do: Our Data and Analytics consultants help clients maximize the value of their ...

Required : • Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph. • 5 years of professional experience in data science, analytics, or data engineering roles ...

Bachelor of Science degree in a relevant field such as statistics, computer science, economics, mathematics, analytics, data science, business, or social sciences * 2-10+ years of experience in data ...

Key Responsibilities Data Science & Analytics * Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints. * Translate business ...

Key Responsibilities Data Science & Analytics * Partner with practice leaders and clients to understand business problems, industry context, data sources, risks, and constraints. * Translate business ...

Data Scientist

Washington, DC · On-site

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Data Scientist

Washington, DC · On-site

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Required : • Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph. • 5 years of professional experience in data science, analytics, or data engineering roles ...

Data Scientist

Washington, DC · On-site

$112K - $179K/yr

Build and integrate data science solutions within the ServiceNow platform, including Performance Analytics, custom applications, and workflow automation * Analyze large, complex datasets to identify ...

Data Scientist

Washington, DC · On-site

$64.98/hr

Minimum of 2 years applying data science/analytics within the health insurance/healthcare industry. * Experience with cloud services such as AWS Sagemaker and MS Azure, and analytic tools including ...

Minimum of 2 years applying data science/analytics within the health insurance/healthcare industry. * Experience with cloud services such as AWS Sagemaker and MS Azure, and analytic tools including ...

Responsibilities The Senior Data Science Analyst shall be able to demonstrate experience and expertise in the following: * Programming languages such as Python(inclusive of libraries that are used in ...

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Data Science Analytics information

See Washington salary details

$27

$62

$106

How much do data science analytics jobs pay per hour?

As of Jun 11, 2026, the average hourly pay for data science analytics in Washington is $62.01, according to ZipRecruiter salary data. Most workers in this role earn between $49.81 and $70.24 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.
What are the most commonly searched types of Data Science Analytics jobs in Washington? The most popular types of Data Science Analytics jobs in Washington are:

Manager of Data Science

CLA (CliftonLarsonAllen)

Arlington, VA • On-site

Full-time

Posted 21 days ago


Job description

Job Summary:
CLA is a top 10 national professional services firm focused on creating opportunities for clients and communities. They are seeking a Manager of Data Science to lead and oversee analytical and AI initiatives, mentor team members, and ensure the delivery of high-quality data solutions.
Responsibilities:
• Provide day‑to‑day leadership, coaching, development, and performance management.
• Mentor and guide analysts, supporting onboarding, skill development, and continuous learning across career stages.
• Conduct workload planning, prioritization, and resource allocation to support multiple concurrent initiatives.
• Build and sustain a high‑performing team culture rooted in collaboration, quality, accountability, and innovation.
• Lead and oversee large scale analytical and AI initiatives, including data acquisition, transformation, modeling, AI system development, automation, and insight generation.
• Provide technical oversight and review of analytical approaches, models, and AI systems to ensure sound methodology, reproducibility, and scientific rigor.
• Guide the development and application of advanced statistical, machine learning, and AI-driven solutions, including predictive models, computer vision, large language models (LLMs), and agent-based systems.
• Lead the design and oversight of AI-enabled systems, including prompt engineering strategies, retrieval-augmented generation (RAG), embeddings, and agentic workflows.
• Establish and evolve analytical and AI best practices, documentation standards, and technical frameworks across the team.
• Ensure standards for model and AI system validation, monitoring, evaluation, documentation, and responsible AI use are consistently applied.
• Partner with engineering, IT, and data platform teams to enable scalable, reliable, and well governed solutions.
• Own delivery outcomes for data science and AI workstreams, ensuring solutions meet quality, performance, and business expectations.
• Translate business objectives into clear analytical and AI priorities, balancing near term delivery with long term capability building.
• Oversee planning, prioritization, and resourcing across projects and teams.
• Monitor solution performance, validation results, and model or AI system stability; guide troubleshooting of complex data, model, or AI issues.
• Ensure solutions are productionized effectively, with clear ownership, monitoring, and integration into business workflows.
• Establish, refine, and enforce standards for documentation, reproducibility, quality assurance, and governance.
• Remove obstacles, manage risks, and ensure consistent execution across initiatives.
• Serve as a primary point of contact for business and functional leaders on analytics and AI initiatives.
• Partner with stakeholders to define business questions, success metrics, analytical frameworks, and delivery expectations.
• Coordinate work across teams, offices, and disciplines to ensure alignment of analytical and AI approaches and outcomes.
• Communicate progress, risks, and results clearly to both technical and non technical audiences.
• Evaluate and recommend adoption of new data sources, technologies, and analytical and AI tools.
• Contribute to enterprise level analytics and AI strategy, including identifying high impact use cases and guiding their transition from concept to production.
Qualifications:
Required:
• 8 years of relevant experience required.
• Experience in data analytics, statistics, data science, AI, financial consulting, computer science or related field required.
• Experience with APIs, web scraping, SQL/no-SQL databases, and cloud-based data solutions required.
• Supervisory experience required.
• Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.
Preferred:
• Degree in Statistics, Computer Science, Economics, Analytics, Data Science (e.g., Informatics, Data Science, Health Data Science), AI, or related field preferred.
• Masters in a Data Science/Analytics/AI is a plus
Company:
CLA exists to create opportunities for our clients, our people, and our communities through industry-focused wealth advisory, outsourcing, audit, tax, and consulting services. Founded in 1998, the company is headquartered in Alpharetta, USA, with a team of 5001-10000 employees. The company is currently Late Stage.