Lead Data Scientist - Marketing Analytics
Zynga is a leading developer of the world’s most popular social games, played by tens of millions of people around the world every single day. To-date, more than 1 billion people have played our games across Web and mobile, including FarmVille, Zynga Poker, Words With Friends, Harry Potter: Puzzles & Spells, Merge Dragons!, Empires & Puzzles, Hit it Rich! Slots, Toy and Toon Blast, and CSR Racing.
The Marketing Analytics team has been charged with supporting audience growth functions across our portfolio. We utilize the vast amount of internal and third-party data available to provide reporting, tooling, and automation solutions that elevate the various functions in Zynga’s Marketing organization. Our roadmap has one purpose: to expand Zynga's ability to reach new audiences.
As a lead data scientist, you will lead our brand marketing function, guiding our efforts to turn data into prescriptive insights with sophisticated analytical and statistical tooling. You will work closely with analytics leadership and marketing professionals to find opportunities, design solutions, and utilize team resources to engineer products. Key to this role will be experience with statistical modeling, especially in the realms of causal inference, econometrics, and media mix modeling. The demands on this team are constantly evolving with the needs of Zynga’s dynamic marketing teams, so it is important that you be able to adapt and utilize resources efficiently.
Collaborate with partner teams to define areas of opportunity and set priorities
Work with team leadership to plan the roadmap and drive initiatives
Coordinate with project management to ensure efficient prioritization
Supervise the larger technical direction of projects
Contribute expertise in product ideation and development
Design and evaluate innovative ways to advance analytics at Zynga
Manage a small team of analytics professionals
Desired Skills and Experience:
Demonstrated experience with some or all of the following: machine learning, data mining, predictive modeling, experimental design, computational analytics/optimization, data visualization, application development
Expertise in statistical frameworks, including causal inference, econometric modeling, and mix media modeling
Excellent presentation and interpersonal skills; comfortable explaining technical topics to non-technical users.
Experience building and executing against a roadmap of critical initiatives
4+ years of work experience in data science, machine learning or analytics roles
Experience with app store optimization preferred
Experience with people management preferred
Proficient in SQL and Python
BS in Computer Science, Math, Statistics, Economics, or other quantitative field; Masters or PhD strongly preferred
Zynga is an equal opportunity employer. We are proud of our diverse community; we do not discriminate on the basis of race, sex, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates, players, employees, and partners from all backgrounds. Join us!
Zynga will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law.
What we offer you:
Zynga Stock RSUs and Bonus Plan
Full medical, dental, vision benefits as well as life insurance
Generous Paid Maternity/Paternity leave
Open vacation policy for all full-time employees
Flexible working hours on many teams
Work alongside driven individuals towards a common goal
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
Hiring Update: The safety of our candidates and team members is our top priority. During the COVID-19 pandemic, our workforce transitioned to working from home, with all interviewing and onboarding being conducted virtually until further notice.