Data Scientist

Company Description

Lotame is a technology company that makes data smarter, faster, and easier to use for digital marketers. Our end‑to‑end data collaboration platform Spherical empowers thousands of marketers, agencies, and media owners to onboard, access, analyze, and activate the data they need to understand and engage consumers. Our proven commitment to industry interoperability, connectivity, and privacy help drive successful business outcomes for companies on their terms.

Lotame is headquartered in the United States and serves global clients in North America, Latin America, Europe, Middle East, Africa, and Asia Pacific.

• Assist with and execute data science projects, working with product, engineering and/or customer service teams to identify requirements, perform analysis, and present results and/or solutions to stakeholders
• Design, develop, test, and refine the statistical algorithms used to power Lotame's business
• Apply knowledge and training in data modeling, data mining and optimization to very large scale data sets, producing solutions to meet Lotame’s business needs;
• Develop and help to productize scalable predictive models in the areas of performance optimization, behavioral profiling, audience segmentation, and identity resolution
• Work alongside other members of the Lotame Data Science team to provide statistical algorithm development and support to a variety of products, including Lotame’s Optimizer and Cross Device
• As a part of a hybrid working community, communicate clearly with team members about progress, blockers, and availability.

• Bachelor’s Degree in Statistics, Mathematics, Engineering or a closely related field;
  Master’s Degree preferred; equivalent knowledge of statistical modeling, machine learning, etc accepted
• Strong fundamental understanding of statistical modeling, machine learning, big data analytics, and algorithmic analysis. Ability to select approaches and algorithms to problems and articulate why those specific solutions are appropriate. This requires some experience and theoretical knowledge
• Comprehension of algorithms in the following areas:
  Bayesian Data Analysis, Classification, Clustering, Regression, Collaborative Filtering, and Graph Algorithms
• Experience with and/or theoretical understanding of distributed computing frameworks, e.g. Hadoop, Map Reduce, MPI. Ideally, some experience with Spark, Amazon EMR, and/or Hive
• Experience working with datasets in a cloud (AWS, Azure, Google) environment, including tools such as EMR, S3, and Athena, while not required, will be beneficial

Base Salary: $73,500.00 - $

Actual compensation within the range will be dependent upon, but not limited to the individual’s skills, experience, qualifications, location and application employment laws. The salary pay range is subject to change and may be modified at any time.

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 needing accommodations to complete the application process. Please reach out to  to request an accommodation.

For San Francisco Bay and Los Angeles Areas: Epsilon will consider for employment qualified applicants with criminal histories in a manner consistent with the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance and San Francisco Police Code Sections , commonly referred to as the San Francisco Fair Chance Ordinance. Applicants with criminal histories are welcome to apply.