The Junior Data Science Analyst is responsible for advanced audience development and technology enablement. The role requires the candidate to sift through big data by leveraging advanced statistical concepts and guide the client into the world of futureproofed technology. Working closely with client stakeholders and internal team leads are vital parts of the role, with accountability for the highest quality execution of a diverse array of client and project deliverables an imperative. The role functions as an expert technical point of escalation, an analytical problem solver, and a technical translator to internal account teams and clients. It provides ongoing strategic account direction/vision for technology, process, and data science.

• Guide the clients in clean room strategy and enable the use of this futureproofed technology
• Propensity model development using ML techniques for net new audiences and refreshes of existing audiences
• QA and troubleshooting of 1P onboarded data to ensure acceptable match rates with client systems
• Advancement of internal modeling practices to improve efficiencies in core hour usage and drive better activation results
• Audience analysis on 1P subscriber segments and collaboration with teams internally on findings
• Index report Python script runs and maintenance for data organization that leads to more efficient analysis
• Translation of technical concepts to non-technical stakeholders via presentations given to clients and vendors
• Guide statistically sound test design that ensures limited to no bias resulting in actionable takeaways
• Keep abreast of evolving media landscape, including research and emerging trends to provide insight to both media teams and client (as required)
• Create and manage deliverables against detailed project plans that align expectations with outcomes
• Provide a high-value consultation layer on top of data science deliverables
• Determine the best means of communicating data science driven insights to clients that ensures understanding of results and application of the analyses is applied
• Build presentations providing clear storyline - why the work is important, the truths that the analytics reveal, and the actions that should follow the analyses
• Grow product delivery and agency revenue organically by cross-selling and up-selling value-add data science products across client divisions, markets, categories, etc.