Interested in this Data Scientist role at EPIC Insurance Brokers & Consultants?
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About This Role
Come join our team!
There are many reasons why EPIC Insurance Brokers \& Consultants has become one of the fastest\-growing firms in the insurance industry. Fueled and driven by capable, committed people who share common beliefs and values and "bring it" every day, EPIC is always looking for people who have "the right stuff" – people who know what they want and aren't afraid to make it happen.
Headquartered in New York City and founded in 2007, our company has over 4,000 employees nationwide. With locations spread out across the U.S., our local market knowledge and industry expertise helps support our clients' regional and global needs. We have grown very quickly since our founding, and we continue to see growth and success thanks to our hard\-working and growth\-minded employees.
Our core values are: Owner mindset, Inspire trust, Think big, and Drive results. If these values and growth align with what you're looking for in your next career? Then consider joining our amazing team!
JOB OVERVIEW:
The Data Scientist role is a unique opportunity for actuaries and data scientists who want to apply analytical rigor to real business challenges while expanding into technology\-enabled solution development. In this role, you will help shape client\-facing and operational analytics that drive smarter decisions across the organization.
Join our Enterprise Data \& Analytics team and play a central role in advancing data analysis, visualization, and innovation across our Property \& Casualty and Employee Benefits businesses. You will work hands\-on to build, validate, and operationalize analyses, dashboards, and analytics applications across EPIC's commercial lines and benefits portfolio. Working within a lean, high\-impact team, you will collaborate closely with solution engineers and business stakeholders to bring analytics into production on the Azure Databricks platform.
LOCATION: Hybrid \- at least 3 days a week in one of our EPIC offices, preferably San Ramon CA but open to any of our office locations *(for a full list, visit:* *https://www.epicbrokers.com/about/locations/)*
WHAT YOU'LL DO:
A detailed list of job duties includes (but is not limited to):
- Collect, integrate, cleanse, and manage data from a variety of insurance\-related sources.
- Perform exploratory data analysis to identify trends, patterns, and actionable insights within complex datasets.
- Develop analytical solutions and process efficiencies using statistical methods, database technologies, and programming tools.
- Create dashboards, visualizations, and reporting assets that communicate insights clearly to business stakeholders.
- Prototype new ideas, support statistical research, and apply data science techniques to address recurring business and data quality challenges.
WHAT YOU'LL BRING:
Required Qualifications
- Bachelor's degree in Computer Science, Mathematics, Actuarial Science, Finance, Insurance, or a related field, or an equivalent combination of education and experience.
- Proficiency with analytical tools and platforms such as Python, SQL, Excel, Tableau, Power BI, or Databricks.
- Experience working with relational databases and applying core data analysis techniques.
- Required: At least 3 years of experience in a data analyst, data science, or comparable analytical role while in an insurance brokerage environment.
- Strong organizational skills with the ability to manage multiple priorities in a self\-directed environment.
- Excellent verbal and written communication skills, with the ability to work effectively across functions.
- Demonstrated problem\-solving ability and sound analytical judgment.
Preferred Qualifications
- Experience in the insurance industry or broader financial services sector.
- Strong intellectual curiosity, a proactive approach to problem\-solving, and exceptional attention to detail.
- Familiarity with hypothesis testing and other statistical evaluation techniques.
COMPENSATION:
The national average salary for this role is $100 000\.00 \- $150 000\.00 in base pay and exclusive of any bonuses or benefits. The base pay offered will be determined based on your experience, skills, training, certifications and education, while also considering internal equity and market data.
WHY EPIC:
EPIC has over 60 offices and 4,000 employees nationwide – and we're growing! It's a great time to join the team and be a part of this growth. We offer:
- Generous Paid Time off
+ Managed PTO for salaried/exempt employees (personal time off without accruals or caps); 22 PTO days starting out for hourly/non\-exempt employees; 12 company\-observed paid holidays; 4 early\-close days
- Generous leave time options: Paid parental leave, pregnancy disability and bonding leave, and organ donor/bone marrow donor leave
- Generous employee referral bonus program of $1,500 per hired referral
- Employee recognition programs for demonstrating EPIC's values plus additional employee recognition awards and programs (and trips!)
- Employee Resource Groups: Women's Coalition, EPIC Veterans Group
- Professional growth \& development: Mentorship Program, Tuition Reimbursement Program, Leadership Development
- Unique benefits such as Pet Insurance, Identity Theft \& Fraud Protection Coverage, Legal Planning, Family Planning, and Menopause \& Midlife Support
- Additional benefits include (but are not limited to): 401(k) matching, medical insurance, dental insurance, vision insurance, and wellness \& employee assistance programs
- 50/50 Work Culture: EPIC fosters a 50/50 culture between producers and the rest of the business, supporting collaboration, teamwork, and an inclusive work environment. It takes both production and service to be EPIC!
- EPIC Gives Back – Some of our charitable efforts include Donation Connection, Employee Assistance Fund, and People First Foundation
- We're in the top 10 of property/casualty agencies according to "Insurance Journal"
To learn more about EPIC, visit our Careers Page: https://www.epicbrokers.com/about/epic\-careers/.
*EPIC embraces diversity in all its various forms—whether it be diversity of thought, background, race, religion, gender, skills or experience. We are committed to fostering a work community where every colleague feels welcomed, valued, respected and heard. It is our belief that diversity drives innovation and that creating an environment where every employee feels included and empowered, helps us to deliver the best outcome to our clients.*
*California Applicants \- View your privacy rights at:* *https://www.epicbrokers.com/wp\-content/uploads/2025/01/epic\-ca\-employee\-privacy\-notice.pdf**.*
*Massachusetts G.L.c. 149 section 19B (b) requires the following statement: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.*
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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 EPIC Insurance Brokers & Consultants, 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. Senior-level AI roles across all categories have a median of $227,400.
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.
EPIC Insurance Brokers & Consultants AI Hiring
EPIC Insurance Brokers & Consultants has 1 open AI role right now. They're hiring across Data Scientist. Based in New York, NY, US.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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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