Associate Director, Advanced Analytics

Adelphi Group; New York (NY); On-site; USD 70,000 - 135,000; Full time

Job summary

Beauty Co-Lab, an Omnicom Media Group unit for L’Oréal USA, seeks a senior data scientist to build causal experimentation models and co-develop advanced statistical learning techniques. You will partner with Planning & Investment to support campaigns across the lifecycle, delivering actionable insights.

Applicants should have a quantitative degree and 5+ years in a media environment, with Python, R, and SQL, and a deep knowledge of Bayesian methods and MMMs.

Qualifications

• University degree in a quantitative field (Statistics, Math, Physics, Economics, CS, or Engineering).
• 5+ years of experience in a media agency, in-house team, or consulting (strongly preferred).
• Experience applying advanced analytics in a media environment with coding in Python, R, SQL; Bayesian approaches, causal experimentation, MMMs.

Responsibilities

• Build causal experimentation models to advance learning agendas.
• Co-develop advanced statistical learning techniques with analytics teams.
• Provide analytics support across the campaign lifecycle with a hands-on and strategic approach.

Skills

Statistical analysis

Bayesian methods

Causal experimentation

Marketing analytics

Education

Bachelor's degree in Statistics / Mathematics / Economics / CS / Engineering

Tools

Python

R

SQL

Job description

Agency:

Omnicom Media

Job Function:

Data and Analytics

Job Subfunction:

Data Science and AI

Job Description:

Beauty Co-Lab (BCL) is a bespoke Omnicom Media Group unit for L’Oréal USA delivering an industry-leading agency solution that drives business growth and transformation. For over a century, L’Oréal has devoted its energy, innovation, and scientific excellence solely to one vocation: Creating Beauty, with the main goal of offering each and every person around the world the best of beauty in terms of quality, efficacy, safety, sincerity, and responsibility to satisfy all beauty needs and desires in their infinite diversity.

At Beauty Co-Lab, our mission is to co-create what’s next, and our team possesses modern media, commerce, and analytical skillsets to keep pace with the rapidly changing ecosystem. We are passionate about beauty, media, data, and technology. With deep expertise in data and technology, we design audience-first, full-funnel, and omni-channel strategies to achieve L’Oréal’s mission: Create the Beauty that moves the world.

The Advanced Analytics team is pivotal to delivering marketing science in the modern agency. Tightly integrated within BCL and L’Oréal, we collaborate across strategy, investment, and brand teams to deliver cutting-edge solutions that blend scientific rigor with commercial applicability.

ROLE DESCRIPTION

EXTERNAL-FACING RESPONSIBILITIES

• Build causal experimentation models to advance L’Oréal’s learning agenda.
• Co-develop best-in-class statistical learning techniques with the L’Oréal Advanced Analytics team to solve complex media challenges.
• Partner with Planning & Investment teams to provide both hands‑on and strategic analytics support across the entire campaign lifecycle.
• Demonstrate excellent project management skills , with the ability to set goals, meet deadlines, and act with a strong sense of urgency without compromising executional excellence.

INTERNAL-FACING RESPONSIBILITIES

• Develop the Advanced Analytics practice knowledge repository and provide guidance to junior members of the team to support the vision.
• Elevate the current analytics methodology by building replicable statistical frameworks that adhere to scientific rigor while maintaining commercial applicability.
• Provide support in media strategy, measurement, and optimization requiring expertise in advanced analytics work, with a special focus on marketing mix models (MMMs).

EDUCATION AND EXPERIENCE

• University degree in a quantitative field like Statistics, Math, Physics, Economics, Computer Science, or Engineering with 5+ years of experience (advanced degree preferred).
• Professional background in a media agency, in‑house marketing team, or management consulting firm (strongly preferred).
• Experience applying advanced analytics within a media environment to solve business problems, including proficiency in coding (e.g., Python, R, SQL), querying databases, and statistical analysis.
• Deep understanding of Bayesian approaches, causal experimentation, media mix modeling, and their commercial application.

ABOUT YOU AND US!

• You have an insatiable appetite for learning, thrive in a fast‑paced environment, and bring a positive attitude to any circumstance.
• You value culture. We are big on creating a fun environment where intellectual curiosity thrives and being a team player isn’t just “nice‑to‑have”—it’s central to our ethos.
• You balance collaboration with conviction. You know when to challenge the norm and when to “disagree and commit.”
• Most importantly, you love analytics! If this describes you, we want to hear from you!
  

New York: $70,000.00-$135,000.00

Omnicom’s policy requires employees to work in the office for a minimum of three days a week, unless additional in‑office days are directed by their agency or manager. Our objective is to increase this requirement over time, and many of our agencies as well as Omnicom’s corporate group already require five days of in‑office attendance.

Omnicom is committed to hiring and developing exceptional talent. We agree that talent is uniquely distributed, and we’re focused on developing inclusive teams that can bring the best solutions to everything we do. We strongly believe that celebrating what makes us different makes us better together. Join us—we look forward to getting to know you. We will process your personal data in accordance with our Recruitment Privacy Notice.

Link to Recruitment Privacy Notice: https://www.omc.com/privacy-notice

For US Job Seekers:

It is the policy of Omnicom and any of its affiliates to provide equal employment opportunities to all employees and applicants for employment without regard to race, religion, color, ethnic origin, gender, gender identity, age, marital status, veteran status, sexual orientation, disability, or any other basis prohibited by applicable federal, state, or local law. EOE/AA/M/D/V/F.