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About This Role
Company Description
A best\-in\-class city that attracts best\-in\-class talent, Philadelphia is an incredible place to build a career. From our thriving arts scene and rich history to our culture of passion and grit, there are countless reasons to love living and working here. With a workforce of over 30,000 people, and more than 1,000 different job categories, the City of Philadelphia offers boundless opportunities to make an impact.
As an employer, the City of Philadelphia values inclusion, integrity, innovation, empowerment, and hard work above all else. We offer a vibrant work environment, comprehensive health care and benefits, and the experience you need to grow and excel. If you’re interested in working with a passionate team of people who care about the future of Philadelphia, start here.
*What we offer*
- Impact \- The work you do here matters to millions.
- Growth \- Philadelphia is growing, why not grow with it?
- Diversity \& Inclusion \- Find a career in a place where everyone belongs.
- Benefits \- We care about your well\-being.
*Agency Description*
The Philadelphia Police Department (PPD) is the nation's fourth largest police department, with over 6300 sworn members and 800 civilian personnel. The PPD is the primary law enforcement agency responsible for serving Philadelphia County, extending over 140 square\-miles in which approximately 1\.5 million reside. Geographically, the Department is divided into twenty\-one police districts (each headed by a captain), which comprise six police divisions (Northwest, Northeast, East, Central, Southwest, South \- each headed by a Divisional Inspector), into two major sections of the city, Regional Operations Command North (ROC North) and Regional Operations Command South (ROC South), each headed by one Chief Inspector under Patrol Operations. Personnel are assigned to work in 55 different locations throughout Philadelphia, with Police Headquarters located in the 6th Police District, in Center City, at 400 North Broad Street.
Job Description
The Police Department is seeking a highly motivated and analytically driven Data Scientist to support data\-informed decision\-making across public safety operations. This position will play a critical role in modernizing data collection through PowerApps, performing advanced analytics using diverse data sources, conducting impact evaluations of crime prevention and enforcement initiatives, and developing dashboards to visualize patterns/trends. The ideal candidate will have a strong background in data science, programming, and public sector analytics, along with the ability to communicate findings to both technical and non\-technical audiences.
Key Responsibilities:
Application Development
- Design, develop, and maintain Microsoft PowerApps and supporting tools to streamline data collection from internal stakeholders (e.g., officers, supervisors, command staff).
- Integrate PowerApps with existing data systems such as RMS, CAD, and internal SQL databases.
- Ensure that data collection tools are secure, user\-friendly, and responsive to field and administrative needs.
Advanced Data Analytics
- Extract, clean, and analyze data from multiple law enforcement and city data systems.
- Develop predictive models and statistical analyses to identify crime patterns, resource allocation inefficiencies, and public safety risks.
- Create dashboards and reports using Power BI, R, or Python to support command\-level decision\-making.
Program Evaluation \& Impact Assessment
- Design and conduct evaluations of crime\-fighting initiatives such as hotspot policing, focused deterrence, or community engagement strategies.
- Apply methods such as matched comparisons, time\-series analysis, or spatial analysis to measure program effectiveness.
- Present findings to department leadership, city officials, and public stakeholders with policy recommendations based on evidence.
Collaboration \& Training
- Work closely with crime analysts, IT, patrol supervisors, and command staff to align data projects with operational needs.
- Partner with academic institutions and vendors on joint research initiatives
- Provide training or support on new tools and methodologies to enhance data literacy across the department.
Qualifications* Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related field
- 3–5 years of experience in data science, analytics, or application development, preferably in government, healthcare, or criminal justice settings
- Experience developing Microsoft PowerApps, including Power Automate and Dataverse integration.
- Proficiency in data analytics tools (e.g., Python, R, SQL), geospatial analysis (e.g., ArcGIS) and visualization platforms (e.g., Power BI).
- Experiences in developing apps using PowerApps and other MS Power Platform
- Experience working with geospatial data and tools in the enterprise setting is a plus
Additional Information TO APPLY: Interested candidates must submit a cover letter, resume and writing sample.
Salary Range: $80,000 \- $90,000
Discover the Perks of Being a City of Philadelphia Employee:
- Transportation: City employees get unlimited FREE public transportation all year long through SEPTA’s Key Advantage program. Employees can ride on SEPTA buses, subways, trolleys, and regional rail for their daily commute and more.
- Parental Benefits: The City offers its employees 8 weeks of paid parental leave.
- We offer Comprehensive health coverage for employees and their eligible dependents.
- Our wellness program offers eligibility into the discounted medical plan
- Employees receive paid vacation, sick leave, and holidays
- Generous retirement savings options are available
- Pay off your student loans faster \- As a qualifying employer, City of Philadelphia employees are eligible to participate in the Public Service Loan Forgiveness program. Join the ranks of hundreds of employees who have already benefited from this program and achieved student loan forgiveness.
- Unlock Tuition Discounts and Scholarships \- The City of Philadelphia has forged partnerships with over a dozen esteemed colleges and universities in the area, ensuring that our employees have access to a wide range of tuition discounts and scholarships. Experience savings of 10% to 40% on your educational expenses, extending not only to City employees but in some cases, spouse and dependents too!
Join the City of Philadelphia team today and seize these incredible benefits designed to enhance your financial well\-being and personal growth!
- *The successful candidate must be a city of Philadelphia resident within six months of hire*
Effective May 22, 2023, vaccinations are no longer required for new employees that work in non\-medical, non\-emergency or patient facing positions with the City of Philadelphia. As a result, only employees in positions providing services that are patient\-facing medical care (ex: Nurses, doctors, emergency medical personnel), must be fully vaccinated.
The City of Philadelphia is an Equal Opportunity employer and does not permit discrimination based on race, ethnicity, color, sex, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, source of income, familial status, genetic information or domestic or sexual violence victim status. If you believe you were discriminated against, call the Philadelphia Commission on Human Relations at 215\-686\-4670 or send an email to [email protected].
For more information, go to: Human Relations Website: http://www.phila.gov/humanrelations/Pages/default.aspx
Salary Context
This $80K-$90K range is in the lower quartile for Data Scientist roles in our dataset (median: $155K across 226 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 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At City of Philadelphia, PA, 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 $192,890 based on 463 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($85K) sits 56% below the category median. Disclosed range: $80K to $90K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
City of Philadelphia, PA AI Hiring
City of Philadelphia, PA has 1 open AI role right now. They're hiring across Data Scientist. Based in Philadelphia, PA, US. Compensation range: $90K - $90K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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