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About This Role
Data Scientist - (196781) At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we foster a culture of inclusion throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world?
Watch Our Story:' https://www.hdrinc.com/our-story'
We believe transportation is more than movement, it’s the foundation of connected, thriving communities. As part of HDR’s Transportation Business Group, you’ll help shape the systems that move people and goods safely, efficiently, and sustainably. From designing resilient highways and iconic bridges to advancing transit, passenger and freight rail, aviation, federal transportation ports and marine infrastructure, your work will directly support economic vitality, public safety, sustainable and resilient communities and quality of life. We bring together planners, engineers, architects, construction management staff, environmental, strategic communications, economists, management consultants and specialists across disciplines to solve complex mobility challenges with innovation, technical excellence, and a deep understanding of community needs. Whether you're modernizing aging infrastructure or pioneering next-generation transportation solutions, your contributions will help define the future of mobility. This isn’t just a job, it’s a chance to lead progress, drive meaningful impact, and leave a legacy of smarter, more connected transportation networks. We are all employee-owners at HDR, which is the foundation of our collaborative culture that connects employees around the world.
Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.
In this role, you will leverage advanced data analytics and low-code development to modernize business processes, enhance operational efficiency, and deliver automated, insight-driven solutions. As a Data Solutions Developer, you will collaborate closely with stakeholders, translate complex requirements into technical solutions, design predictive models, and build applications and automations that support strategic organizational goals. This role requires strong analytical capability, technical expertise, and the ability to manage sensitive information with professionalism and discretion.
In the role of Data Scientist, we'll count on you to:
- Data & Analytics + Analyze complex datasets to identify patterns, trends, and opportunities that improve business decisions. + Develop data products including reports, dashboards, and visualizations to communicate business insights and KPIs. + Perform data acquisition, cleaning, transformation, and exploratory data analysis (EDA). + Engineer features and transform raw data into structured attributes for machine learning models. + Build and maintain advanced predictive models (classification, regression, time series, neural networks, NLP, computer vision). + Manage the end-to-end model lifecycle: development, deployment, monitoring, drift detection, retraining, and inference. + Tune models and conduct rigorous validation, testing, and quality evaluation. + Apply predictive models to enhance operational and business outcomes.
- Automation, Low-Code Development & Process Optimization + Leverage Microsoft Power Platform (Power Apps, Power Automate, Power BI, etc.) to build business applications, automate workflows, and improve operational efficiency. + Optimize business processes by mapping current (“as-is”) and future (“to-be”) workflows and reengineering processes aligned to organizational goals. + Conduct root-cause analysis to identify process inefficiencies and propose technology-driven remedies. + Align automation strategies with project objectives and implement scalable automation solutions. + Collaborate on UI/UX design considerations to ensure applications and dashboards are intuitive and user-friendly. + Develop technical documentation, including SDLC artifacts, workflow diagrams, user guides, and requirements specifications. + Participate in unit testing, Quality Assurance (QA), and Quality Control (QC) activities to ensure solution reliability.
- Systems, Technology & Collaboration + Contribute to system, software, or platform implementation efforts by supporting development, testing, rollout, and user adoption. + Work with IT, Infrastructure Technology, and Operational Technology teams to align analytics and automation capabilities with enterprise systems. + Build dashboards and business intelligence solutions that track project health, KPIs, and performance metrics. + Use collaboration tools (SharePoint, Teams, PowerApps) to support project communication, knowledge management, and version control. + Engage with customers and stakeholders to gather business requirements and deliver a strong customer experience.
Position is based on-site at a client office in Alexandria, VA.
Preferred Qualifications
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Information Technology, or
a related field
- A minimum of 5 years experience strongly preferred
- Transit experience preferred
- WMATA experience preferred
Due to client contract requirements US citizenship or naturalized citizenship is required. This position is also subject to a governmental background check.
Required Qualifications* A degree in a closely related field or combination of education and relevant experience
- A minimum of 3 years experience with data engineering tools and languages such as SQL, Power Query, and Pandas
- A minimum of 3 years experience with business intelligence tools such as Power BI, Tableau, Plotly, Seaborn, and Matplotlib
- A minimum of 3 years experience with data science languages such as Python and R
- Self-motivated, detail-oriented professional, ability to multitask a must
- Proficiency with MS Office including Word and Outlook
- Ability to handle confidential information
- Excellent writing and people skills
- Strong math and organizational skills
- Flexibility and ability to prioritize and handle multiple tasks and various managers in a fast-paced environment
- Excellent verbal and written communication skills including grammar, punctuation, proofreading, spelling and telephone skills
- An attitude and commitment to being an active participant of our employee-owned culture is a must
- In-depth knowledge of machine learning algorithms, statistical models, and data analytics
- Experience completing multiple data science projects
What We Believe
HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve.
Our Commitment
As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day.
Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees.
We provide a comprehensive benefits package that promotes employee ownership, employee health, performance, and success, which includes medical, dental, vision, short and long-term disability, life insurance, an employee assistance program, paid time away, parental leave, paid holidays, a retirement savings plan with employer match, employee referral bonus and tuition reimbursement. The expected compensation range for this position depends upon skills, experience, education and geographical location. (Stated benefits are for full-time regular positions. Temporary and part-time roles eligible for limited benefits.) Washington, DC: $100,044 - $142,920.Primary Location
: United States-District of Columbia-Washington DCIndustry
: Highway + RoadSchedule
: Full-timeEmployee Status
: Regular BusinessClass: Data and AutomationJob Posting
: Oct 6, 2026
Salary Context
This $100K-$142K range is in the lower quartile for Data Scientist roles in our dataset (median: $167K across 172 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 9,653 AI roles we're tracking, Data Scientist positions make up 5% of the market. At HDR, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $190,000 based on 1,406 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($121K) sits 36% below the category median. Disclosed range: $100K to $142K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
HDR AI Hiring
HDR has 1 open AI role right now. They're hiring across Data Scientist. Based in Washington, DC, US. Compensation range: $142K - $142K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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