Lead Data Scientist

As Data Scientists, we work with business leaders to solve clients’ business challenges and improve clients’ marketing results. We contribute our Advanced Data Science subject matter expertise to the recommendations and solutions delivered to our clients. We spend the majority of our time on getting data into proper shape, performing statistical analyses, developing predictive models and machine learning algorithms to solve clients’ business problems. We evaluate different sources of data, discover patterns hidden within raw data, create insightful variables, and develop competing models with different machine learning algorithms. We validate and cross validate our recommendations to make sure they will perform well over time.

The ideal candidate will be eager to engage clients, drive innovation through experience, and will be someone who is strong at both “doing” and collaborating with other members of the team.

Requirements

• 3+ years of marketing analytics experience within a consulting, advertising, ad-tech firm, or media agency
• 2+ years experience building with bayesian linear regression models or Marketing Mix Models with the ability to train the models
• Experience with media data is required, with experience with platforms and customer data from either the media agency, technology, or brand side.
• Understanding of ad technologies and how they are evolving in the new media landscape and the roles of different addressable tactics – TV, CRM, mobile, search, display, etc.
• Manage, mentor and motivate direct reports to encourage their professional development while providing hands on, daily supervision and guidance
• Proven ability to manage client expectations, delivery, and provide thought leadership
• Comfortable working in a fast-paced team environment
• MS degree in Statistics, Math, Data Analytics, or a related quantitative field
• Experience running different types of statistical models such as linear regression, logistic regression, random forest, mixed models and various Bayesian modeling techniques
• Background across multiple verticals
• Working within an advertising platform such as Facebook, Google, Amazon
• Familiarity with Clean Room Solutions
• Experience with one or more Data Science software languages (Python, R, SAS)
• Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural- or pipeline-approaches.
• Experience with SQL and relational databases, query authoring (SQL) and tuning as well as working familiarity with a variety of databases including Hadoop/Hive
• Comfortable with cloud-based platforms (AWS, Azure, Google)