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About This Role
About the Position
We're seeking a Reporting Data Scientist to support large, complex infrastructure programs, including highways, roads, bridges, transit (rail and bus), international airports, and water/wastewater projects delivered through both traditional and alternative project delivery methods. This role will support enterprise\-level project controls and program management functions by developing advanced analytics, predictive models, automated reporting solutions, and executive dashboards that transform complex project, program, financial, cost, schedule, and risk data into actionable business intelligence. The successful candidate will help drive data\-informed decision\-making across some of the nation's largest infrastructure programs. Based on the source materials, this role will support program\-wide analytics, forecasting, reporting automation, and visualization initiatives within a Project Controls organization.
This is a long\-term, full\-time, on\-site position located in Sacramento, CA.
Responsibilities *may include, but are not limited to, the following:*
- Develop, maintain, and continuously improve enterprise\-level data models, analytics frameworks, reporting workflows, and performance measurement systems.
- Build predictive, statistical, and forecasting models supporting cost, schedule, risk, and program performance management.
- Design, develop, and maintain Power BI dashboards, visualizations, and automated reporting solutions for executive leadership and project stakeholders.
- Analyze large and complex datasets to identify trends, risks, anomalies, performance drivers, and opportunities for process improvement.
- Partner with project controls, scheduling, cost management, risk management, finance, and program management teams to integrate data from multiple sources and produce unified analytical outputs.
- Support monthly, quarterly, and executive\-level reporting cycles through preparation, validation, and analysis of project and program data.
- Identify opportunities to automate manual reporting processes and improve data accessibility, quality, and efficiency.
- Establish and maintain data governance, quality assurance, and validation procedures to support reliable decision\-making.
- Collaborate with project teams and stakeholders to collect, validate, consolidate, and interpret data from multiple systems and platforms.
- Present analytical findings, dashboard insights, trends, and recommendations to executive management and other stakeholders.
- Support board\-level reporting requirements and strategic program performance initiatives.
- Contribute to PMIS, reporting, analytics, and business intelligence improvements across major capital infrastructure programs.
Attributes
- Excellent written and verbal communication and interpersonal skills.
- Excellent analytical thinking, problem\-solving, and data storytelling capabilities.
- Collaborative mindset that fosters teamwork, trust, positive relationships, and effective coordination across cross\-functional stakeholders.
- Strong organizational skills with the ability to manage multiple priorities and deadlines simultaneously.
- Strong attention to detail and commitment to accuracy, quality, accountability, and continuous improvement.
Minimum Qualifications
- Master's degree in data science, computer science, statistics, engineering, business analytics, or related field.
- 8\+ years of experience performing data analytics, business intelligence, reporting, predictive modeling, or data science functions in large infrastructure construction programs, collaborating with (at a minimum) program controls, program scheduling, and program risk management teams.
- Experience supporting major capital infrastructure, transportation, transit, aviation, water/wastewater, or construction programs.
- Strong knowledge of project controls, management reporting, business intelligence, data management, and performance measurement methodologies as they relate to heavy civil infrastructure programs.
- Demonstrated experience developing executive\-level reporting, dashboards, analytics, and data visualization solutions.
- Experience implementing data strategies, analytics workflows, reporting processes, and data governance practices.
- Experience integrating data from multiple systems and sources to create unified reporting and analytical outputs.
- Experience developing predictive models, forecasting tools, statistical analyses, and performance metrics.
- Strong proficiency with Python, R, SQL, or similar programming and analytics tools.
- Proficiency with Power BI and other dashboarding, visualization, and business intelligence platforms.
- Proficiency with Microsoft Office Suite/Office 365 (e.g., Outlook, Teams, Word, Excel, PowerPoint, etc.).
Preferred Qualifications
- Project Management Professional (PMP), Microsoft Power BI Data Analyst, Google Data Analytics, MBA, or similar professional certification.
- Experience leading analytics initiatives or contributing to analytics/reporting teams supporting major infrastructure programs.
- Experience supporting project controls, cost management, scheduling, risk management, or PMO functions.
- Experience developing Kanban\-style, Agile, or workflow visualization dashboards.
- Experience with PMIS, Oracle, Primavera P6, enterprise reporting platforms, or large\-scale business intelligence environments.
- Proficiency with desktop publishing software, Visio, and professional graphics software.
Compensation Details
Expected Salary: $140k\-$210k/year ($67\-$101/hour). Luster provides the salary range that the company in good faith believes it might offer for this position based on the successful candidate's level of experience, knowledge, skills, abilities, education, certifications, licenses, geographic location, etc. Luster reserves the right to ultimately pay more or less than the posted range depending on circumstances not related to any status protected by local, state, and/or federal law.
Just LOOK at the Benefits We Offer!
- Unlimited flexible time off
- Paid holidays
- Paid parental leave
- Health, dental, and vision insurance
- Flexible spending accounts (healthcare and dependent or elder care)
- Long\-term disability insurance
- Short\-term disability insurance
- Life insurance and accidental death and dismemberment
- 401(k) plan with guaranteed employer contribution
- Formal career planning and development program
- $2,500 annually toward professional development
- Wellness program with monthly wellness stipend
- Company cell phone or cell phone plan reimbursement
- Free personalized meal planning and nutrition support with a registered dietitian
- Free personal financial planning services
- Employee assistance program
- Employee discounts
- Employee referral bonus
Specific plan details and coverage for each benefit noted above will be provided upon offer. *\#IN\-LNJS*
If you wish to be considered for a position where there is not an active job posted, please search for our 'General Application' and apply.
Luster is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to criminal history, race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E\-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I\-9 to confirm work authorization.
All positions may be subject to a background check and drug test once a conditional offer of employment is made for any convictions directly related to its duties and responsibilities, in accordance with all applicable local, state, and/or federal regulations.
This job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required for the position.
Luster does not accept unsolicited resumes from any third\-party. In the absence of a signed agreement, Luster will not consider or agree to payment of any kind. Any unsolicited resumes presented to Luster personnel, including those submitted to Luster hiring managers, are deemed to be the property of Luster.
Please email [email protected] for accommodations necessary to complete the application process.
Salary Context
This $139K-$210K range is above the median for Data Scientist roles in our dataset (median: $157K across 236 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 3,823 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Luster National, 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 $198,000 based on 808 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($174K) sits 12% below the category median. Disclosed range: $139K to $210K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Luster National AI Hiring
Luster National has 1 open AI role right now. They're hiring across Data Scientist. Based in Sacramento, CA, US. Compensation range: $210K - $210K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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