Manager, Data Science at Omnicom Media Group US H&S

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

09 Mar, 26

Salary

110000.0

Posted On

09 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, R, Machine Learning, Causal Models, Presentation Skills, Communication Skills, Digital Clean Rooms, Marketing Science, Data Analysis, Audience Segmentation, Campaign Performance, Process Efficiencies, Analytical Results, Knowledge Repository, Client Interaction

Industry

Advertising Services

Description

The Company: Hearts & Science has been inspired by confident marketers seeking business advantage in a world of personalized digital marketing, where CRM and addressable channels converge, and decisions must be made in real time to aggregate effective reach and deliver the right message at the right time. Designed to inform brand strategies with real-time insights, Hearts & Science is a data-driven marketing agency with expert media planning and buying capabilities, among other services that include shopper marketing, marketing innovation and content activation. The Data Science team is pivotal in the delivery of modern agency services. We are tightly integrated with marketing science teams to deliver on and exceed our clients’ business goals. Responsibilities External facing responsibilities: Build advanced ML models to cluster and segment audiences, scale and deploy custom audiences across various platforms/ publishers Run descriptive and diagnostic analyses to help measure campaign performance within clean rooms and/or other analytics platforms (e.g., Google ADH, Facebook advanced analytics, Amazon Marketing Cloud, etc.) Adhere to set deadlines and ensure high quality work product Internal facing responsibilities: Leverage technical (coding) skills to help bring about process efficiencies Contribute to building decks and reports that help translate analytical results to internal and client teams Contribute to building DS Practice knowledge repository via decks, documents and other artifacts Required Skills Hands-on programming language skills (SQL, Python, R, etc) Intermediate exposure to machine learning techniques, causal models, etc. to support the analysis of information Advanced presentation and communication skills Some experience working with non-technical teams Knowledge of digital clean rooms, and their related concepts and strategy Certifications in any of the following: Meta (Blueprint), SQL, Python, R (online) Demonstrated domain knowledge of business/industry Education and Experience A university degree in mathematics, computer science, statistics or related field, and 3-5 years of experience in informatics work in academia, advertising, management consulting, marketing or digital consulting Knowledge of agency-side execution process is desirable, but not required #LI-CC2 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 $70,000—$110,000 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. Review Our Recruitment Privacy Notice

Responsibilities

The Manager, Data Science will build advanced machine learning models for audience segmentation and analyze campaign performance using various analytics platforms. They will also leverage technical skills to improve processes and contribute to internal and client reporting.