Senior Data Scientist (L5), Games
Data Science and Engineering ('DSE') at Netflix is aimed at using data, analytics, and sciences to improve various aspects of our business. We are looking for a Senior Data Scientist to join our Games DSE team, leading experimentation and advanced data science needs. This role will be partnering closely with our Game studio stakeholders to drive data informed decisions by building predictive models, conducting statistical analysis and deriving business insights. As a member of this team, you will also play a critical role in presenting insights that shape our decision making and ensure decisions are sound from a statistical perspective.
What You Will Do:
• Partner with our Game stakeholders (e.g., Netflix Games Development team, Game Developers, Game Strategy, Planning & Analysis team) on advanced analytic initiatives (e.g., prediction modeling, causal inference, experimentation etc)
• Lead the design, analysis, and interpretation of experiments that shape decision-making around Games at Netflix
• Proactively perform data exploration to discover innovation and testing opportunities
• Drive and implement high impact projects end to end
• Present your research and insights to key stakeholders
• Work with business stakeholders to connect analysis to key decisions that affect the business to influence and drive impact to the business
• Balance handling ad hoc requests while also driving larger projects forward
Who You Are:
• You have at least 2 years of experience working in the Games industry as a Data Scientist.
• At least 5 years of experience with a PhD degree in Statistics, Econometrics, Mathematics, Engineering or a relevant quantitative field or 8+ years of experience with a Master degree in those fields.
• You have statistical skills utilized in A/B testing, analyzing observational data, and statistical modeling
• You are comfortable working with large data sets and analyzing complex data with SQL and other tools such as Python or R
• You have good business acumen on product innovations and excellent problem solving skills to translate business requirements to data science problems.
• You have a strong bias to action, delivering results quickly with iteration instead of waiting for perfection
• You are a fast learner and are comfortable with ambiguous requests.
• You have exceptional communication skills and can manage stakeholder priorities directly
• Willing to mentor junior data scientists on the team to accelerate team growth.
Our culture:
You can learn more about Netflix's unique culture of Freedom and Responsibility, that presents an opportunity to work with some of the best and the brightest, allowing you to make a difference to our business in a meaningful way.
At Netflix, we carefully consider a wide range of compensation factors to determine your personal top of market. We rely on market indicators to determine compensation and consider your specific job, skills, and experience to get it right. These considerations can cause your compensation to vary and will also be dependent on your location.
The overall market range for this role is typically $170,000 - 720,000.
This market range is based on total compensation (vs. only base salary), which is in line with our compensation philosophy. Netflix is a unique culture and environment. Learn more here.
Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.
We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.
Job is open for no less than 7 days and will be removed when the position is filled.
Jobcode: Reference SBJ-36j32x-161-123-152-244-42 in your application.
