Senior Associate, Data Science

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 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 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

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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, and STD/LTD insurance benefits.

Compensation Range

$40,000-$85,000 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.

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