Zenith is The ROI Agency, we succeed when our clients succeed. We have a simple strategy: motivate our people, deliver great work, and delight our clients. Clients want to work with happy and motivated people.  We have a superb Talent team, helping the agency recruit, develop and retain the industry's best talent. We're constantly striving to create a winning culture and we're delighted that 91% of our people would recommend us as a great place to work.  We are single mindedly focused on delivering great work. We have a consistent track record of making our clients' communications more effective. Our goal is to achieve commercial marketing success. We don't set out to win awards but see them as a function of great work.  Our greatest credential is our client list. Every day we work on challenging business and communication issues, in partnership with great client marketing teams. We are proud to have worked with many of our clients for 10 years or more and are equally proud of our new relationships.  To learn more, visit www.zenithmedia.com

What does Zenith Data Sciences do?

Working closely with both the Business Planning and Analytics teams, Data Sciences designs and implements statistical models and machine learning solutions that tie our clients’ marketing to real-world business goals. We use these models to understand past performance, predict future performance, and inform and optimize future decisions. Our work brings our clients closer to their marketing, helping them understand if they are talking to the right people in the right way.
 

What does a successful Data Scientist look like?

We don’t all look the same, and we don’t expect you to, either. But a successful Data Scientist should share our passion for emerging tech and media, bring an evidence-based approach to decision-making, determine a point of view and share it in a positive way, gear up for a challenge, and always crave to learn more and improve. We are looking for prior experience in marketing analytics, especially digital creative and media, but this isn’t necessarily a requirement. At least 1-2 years of prior professional experience is highly desired.
 

What does a Data Scientist do day-to-day?

Data Scientists form the foundation of the Data Sciences team, structuring and analyzing data, implementing and interpreting models that feed business-improving insights, and putting it all together into presentations that bring the story to life for our clients. Data Scientists work closely with the Data Science Manager to help execute the broader vision for their account, and to continually evolve our Data Science solutions. Day-to-day responsibilities include:

• Design, estimate, tune, score and maintain advanced statistical and mathematical models (e.g. classification, numeric forecasts, customer segmentation, customer propensity, attribution, etc.).
• Produce accurate statistical analysis and ensure high quality of the data analysis produced.
• Interpret, document and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations.
• Take analytical objectives and define data requirements. Extract, clean, and transform both customer level, and aggregated data for analysis, modelling, segmentation and reporting.

Data Science Training and Experience:

• BS/MS degree in quantitative field (mathematics, physical science, engineering, statistics, economics)
• 2+ years business experience working on data science projects.

Data Science Technical Skills:

• Strong understanding of mathematical modeling, probability, and statistics including
• Linear/logistic regression, decision trees, and optimization modelling.
• Experience with developing and applying advanced statistical methods to analytical problems including analysis of time series.
• Data Science Technical Tools:
• Proficient with Python/R/SAS/SPSS for statistical modeling and machine learning.
• Familiarity with Relational Databases and SQL programming
• Familiar with data processing and management support tools such as MS Office, advanced excel analysis, Power BI, Tableau
• Soft Skills:
• Strong written and verbal presentation skills.
• Proactive, collaborative, adaptable, willing to expand technical and business skills.