Senior Associate, Data Science

Omnicom Media; New York (NY); Hybrid; USD 45,000 - 75,000; Full time

Benefits offered by this job

Health insurance

Vision insurance

Dental insurance

401(k)

Healthcare FSA

Dependent Care FSA

Vacation days

Sick days

Personal days

Paid parental leave

Paid medical leave

STD/LTD insurance

Job summary

Omnicom Media’s Beauty Co-Lab unit in New York seeks a data scientist to drive data-driven marketing insights for L’Oréal USA. You will work with strategists and media buyers to shape client plans, building utilities, and improving methodologies.

The role requires 1–2 years of experience, SQL/Python proficiency, and cloud experience (GCP or AWS). Benefits include health, vision, dental, and 401(k). Hybrid work arrangement with some in-office days.

Qualifications

• 1 to 2 years of relevant experience
• Hands-on expertise in SQL and Python
• Experience with cloud computing such as Google Cloud Platform or AWS
• Bachelor's degree in statistics, mathematics, economics, engineering, information management, social sciences, or business/marketing related fields

Responsibilities

• Explore and analyze datasets to derive insights for client-specific and general solutions
• Uncover audience insights for clients and guide non-technical stakeholders in analysis choices
• Independently formulate and execute analytics plans and iterate with client feedback
• Translate quantitative results into actionable insights and storytelling
• Perform hands-on machine learning and statistical modeling for audience segmentation/extension
• Collaborate to build tools that process, visualize, and analyze data for sharing across teams
• Evaluate new data/tools and navigate platforms to extract/load data from partner cloud storage
• Document and share knowledge with L’Oréal & BCL teams

Skills

SQL

Python

Education

Bachelor's degree in statistics, mathematics, economics, engineering, information management, social sciences, or business/marketing related fields

Advanced quantitative degree or intensive bootcamp experience

Tools

Google Cloud Platform

AWS

Job description

Agency

Omnicom Media

Job Function

Data and Analytics

Job Subfunction

Data Science and AI

Job Description

About the Job

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.

With deep expertise in data and technology, we deliver audience first, full-funnel and omni-channel strategies to deliver against L'Oréal's mission: Create the Beauty that moves the world.

For over a century, L’Oréal has devoted its energy, innovation, and scientific excellence solely to one vocation: Creating Beauty with a main goal of offering each and every person around the world the best of beautyin 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 of beauty champions and media challengers possess modern media, commerce, and analytics skillsets to keep pace with the rapidly changing ecosystem and reflect the wonderful diversity of the consumers and communities we serve. We are passionate about beauty, media, data, and technology.

About BCL Data Science: We are a team of engaged, data-curious professionals who continuously seek new and improved ways to create value for our clients. We share ideas, code, outcomes, and credit for our collective efforts. We're looking for explorative, independent data scientists to grow with us as we tackle ever-changing challenges.

Responsibilities

As a member of the BCL data science team, you will work with client team strategists and media buyers to create solutions that shape the strategic direction of your client’s marketing plans through data-driven insights. You will collaborate with other data scientists to build new utilities, improve methodologies, and explore a wide variety of datasets. This work may involve:

• Exploring and experimenting with datasets to draw insights and search for client-specific and general solutions


• Uncovering audience insights for clients:
  
  
  
  • Guiding non-technical stakeholders in choosing the right analysis to answer open-ended questions
  
  
  • Independently formulating and executing an analytics plan; iteratively building on client feedback to get to a satisfactory answer
  
  
  • Translating quantitative results back into actionable insights and interesting storytelling
  
  
  
  


• Hands-on machine learning and statistical modeling for audience segmentation/extension


• Collaboratively ideating and building tools that process, visualize, and analyze data to share across the organization


• Evaluating new data and tools; quickly learning to navigate new platforms; extract, transform, and load data from various partner cloud storage solutions


• Documenting and sharing knowledge with a wide variety of L’Oreal & BCL teams

Education & Experience

• 1 to 2 years of relevant experience


• Bachelor’s degree in statistics, mathematics, economics, engineering, information management, social sciences, or business/marketing related fields. Advanced quantitative degree or intensive bootcamp experience is preferred.


• Must have hands-on expertise in SQL and Python


• Experience with cloud computing such as Google Cloud Platform or AWS

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 relevant experience, other job-related qualifications/skills, and geographic location (to account for comparative cost of living). The Company reserves the right to modify this pay range at any time.

For this role, benefits include:

• health insurance


• vision insurance


• dental insurance


• 401(k)


• Healthcare Flexible Spending Account


• Dependent Care Flexible Spending Account


• vacation days


• sick days


• personal days


• paid parental leave


• paid medical leave


• STD/LTD insurance benefits

Compensation Range

$45,000—$75,000 USD

This role is hybrid, requiring three (3) days per week in the office. The remaining two (2) days may be worked remotely. Specific in-office days will be discussed during the interview process, with flexibility to align with team needs. Please note that the number or required in-office days may be adjusted over time, potentially increasing the number of required in-office days based on business needs.

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.

Compensation Range

$45,000—$75,000 USD

This role is hybrid, requiring three (3) days per week in the office. The remaining two (2) days may be worked remotely. Specific in-office days will be discussed during the interview process, with flexibility to align with team needs. Please note that the number or required in-office days may be adjusted over time, potentially increasing the number of required in-office days based on business needs.