Interested in this Data Scientist role at Epsilon?
Apply Now →Skills & Technologies
About This Role
Company Description
Overview
Epsilon's Data Science & AI practice within Analytics Services team is seeking a Senior Staff Data Scientist to lead the delivery of advanced analytics and AI solutions that drive measurable business impact for our clients.
The Analytic Services team works on client engagements and related delivery for Epsilon product platforms. The team partners with clients, agencies and data providers, leveraging analytics, data science, digital measurement and emerging AI capabilities to drive strategic thought and effective decision making. The Senior Staff Data Scientist will lead a portfolio of analytics programs across client accounts, own end-to-end delivery and business impact, and serve as a senior thought partner to clients, account teams and internal leadership. This role combines strong technical depth, people leadership, client-facing executive presence and the ability to translate complex data into measurable marketing and business outcomes.
Responsibilities
Operational
- Own end-to-end delivery of analytics programs across multiple client accounts, from scoping and solution design through execution, measurement and business impact articulation
- Partner with analytic consulting teams, clients and account teams to translate agreed business objectives and analytical roadmaps into scalable analytical solutions, measurement frameworks and actionable insights.
- Develop and govern analytical frameworks for customer segmentation, propensity modeling, customer lifetime value, campaign measurement, attribution, churn prediction and marketing effectiveness
- Lead complex, cross-functional initiatives across analytics, data engineering, product, technology and client teams to ensure high-quality, on-time and on-budget delivery
- Provide oversight and quality assurance for statistical analyses, machine learning models, experimental designs, measurement frameworks and insight narratives
- Translate complex analytical findings into clear, compelling executive-level stories and recommendations that demonstrate measurable client business impact
- Provide technical leadership and analytics subject-matter expertise supporting pre-sales opportunities, solutioning, proof of concepts and proposal development in partnership with analytic consulting and account teams.
- Champion the adoption of scalable analytics, automation, reusable assets and emerging AI or GenAI capabilities to improve delivery efficiency and solution quality
- Guide teams in hands-on analysis of large-scale first-party, third-party and platform data, ensuring statistically valid outputs and actionable insights
- Ensure strong project governance through clear communication, risk management, collaborator alignment, documentation and proactive expectation management
Functional
- Lead, manage, mentor and grow a high-performing team of data scientists across multiple client engagements.
- Define team goals, manage performance outcomes, provide regular coaching and create structured development plans for team members.
- Provide thought leadership to strengthen analytical methods, delivery processes, reusable frameworks and best practices across the team
- Drive hiring, onboarding, capability building and succession planning in alignment with organizational growth priorities
- Foster a culture of analytical rigor, accountability, innovation, collaboration, experimentation and continuous learning.
- Ensure team engagement, utilization and delivery excellence across billable projects and critical initiatives
- Guide the team to follow all policies and procedures for project documentation, tracking specifications, QA/QC, data governance, platform access and client communication.
- Collaborate effectively with cross-functional internal teams, senior collaborators, global partners and client teams to drive measurable digital marketing and business outcomes.
Qualifications
- Bachelor's degree, or higher, in a quantitative field such as Engineering, Statistics, Economics, Mathematics, Computer Science, Marketing Analytics or a related field; master's degree preferred.
- Minimum 10+ years of experience in analytics, digital media analytics, marketing analytics or related consulting roles, with demonstrated experience leading client-facing analytics programs.
- Proven experience leading and developing teams, including goal setting, performance management, coaching, feedback communication and capability building.
- Strong hands-on and leadership experience with Python, SQL and Databricks mandatory; Experience with Adobe Analytics, Google Analytics, Power BI and Tableau platforms would be an added advantage.
- Deep understanding of funnel analysis, attribution, customer journey analytics, audience segmentation, cohort analysis, campaign measurement and experimentation.
- Strong understanding of digital marketing channels and concepts, including SEO, SEM, paid media, conversion rate optimization, content performance and campaign performance measurement.
- Ability to guide teams through complex analytical problem solving, hypothesis development, data exploration, tracking validation, insight generation and business recommendation.
- Strong executive communication skills with the ability to present complex analytical findings to senior partners through clear storytelling and visually compelling presentations.
- Excellent partner management, client relationship, consulting, prioritization and negotiation skills.
- Solid planning, resource management and project governance skills, with experience managing multiple programs, workstreams and teams concurrently.
- Strong attention to detail and commitment to analytical quality, tagging accuracy, data validation, reproducibility, documentation and QA/QC standards.
- Demonstrated ability to drive innovation, process improvement and adoption of new tools, technologies, AI capabilities and analytical methodologies.
- Highly collaborative, accountable and motivated leader with strong interpersonal skills and a passion for solving complex client business problems through digital data and analytics.
Click here to view how Epsilon transforms marketing with 1 View, 1 Vision, 1 Voice.
Additional Information
When you join Epsilon, we'll create something EPIC together. We're a global leader in data and identity, with deep expertise in digital media, clean rooms, customer data platforms, loyalty and marketing services. Positioned at the center of Publicis Groupe, Epsilon helps brands deliver personalized experiences at scale and build lasting customer relationships by unlocking the full potential of data and identity. Epsilon operates in 30+ countries across EMEA, the Americas and APAC, with more than 8,000 employees.
Check out a few of these resources to learn more about what makes Epsilon so EPIC:
Our Culture: https://www.epsilon.com/us/about-us/our-culture-epsilon
Life at Epsilon: https://www.epsilon.com/us/about-us/epic-blog
Epsilon has five values that define our culture and guide us as we create value for our clients, our people and consumers. We seek candidates who align with our company values, demonstrate them and make them meaningful in their day-to-day work:
- Act with integrity. We are transparent and have the courage to do the right thing.
- Work together to win together. We believe collaboration is the catalyst that unlocks our full potential.
- Innovate with purpose. We shape the market with big ideas that drive big outcomes.
- Respect all voices. We embrace differences and foster a culture of connection and belonging.
- Empower with accountability. We trust each other to own and deliver on common goals.
Because You Matter
As an Epsilon employee, you deserve perks and benefits that put you, your family and your finances first. Our benefits encompass a wide range of offerings, including but not limited to:
- Time to recharge: Flexible time off (FTO), 14 paid holidays, paid sick time
- Family well-being: Parental/new child leave, childcare & elder care assistance, adoption assistance
- Extra perks: Comprehensive health coverage, 401(k), tuition assistance, commuter benefits, professional development, employee recognition, charitable donation matching, health coaching and counseling
Epsilon benefits are subject to eligibility requirements and other terms.
Epsilon is an Equal Opportunity Employer. Epsilon's policy is not to discriminate against any applicant or employee based on actual or perceived race, age, sex or gender (including pregnancy), marital status, national origin, ancestry, citizenship status, mental or physical disability, religion, creed, color, sexual orientation, gender identity or expression (including transgender status), veteran status, genetic information or any other characteristic protected by applicable federal, state or local law. Epsilon also prohibits harassment of applicants and employees based on any of these protected categories. Epsilon will provide accommodations to applicants who need accommodations to complete the application process. Please reach out to [email protected] to request an accommodation.
For San Francisco Bay and Los Angeles Areas: Epsilon will consider qualified applicants with criminal histories for employment in a manner consistent with the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance and San Francisco Police Code Sections 4901-4919, commonly referred to as the San Francisco Fair Chance Ordinance. Applicants with criminal histories are welcome to apply.
#LI-BB1
Compensation Range: USD $112,800.00 - USD $238,700.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 10/12/2026.
Salary Context
This $112K-$238K range is above the median for Data Scientist roles in our dataset (median: $167K across 150 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 8,943 AI roles we're tracking, Data Scientist positions make up 4% of the market. At Epsilon, 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. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($175K) sits 8% below the category median. Disclosed range: $112K to $238K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
Epsilon AI Hiring
Epsilon has 1 open AI role right now. They're hiring across Data Scientist. Based in New York, NY, US. Compensation range: $238K - $238K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.