Data Scientist (L4) - Marketing and Experience DSE

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

It's an exciting time to join Netflix as we continue to transform entertainment globally. We are bringing new stories to millions of people worldwide by promoting our original, exclusive content. As we move beyond 300 million members and hundreds of partnerships worldwide, our approach to marketing is to build innovative, culturally relevant, creatively excellent campaigns that pierce the zeitgeist and drive conversation.

Our Experiences team puts fans at the center of their favorite stories, in real life, through permanent entertainment venues, Netflix House, and touring attractions around the world. Netflix Houses are our permanent, always-on, constantly refreshable entertainment venues, where guests can step into their favorite stories. We want these experiences, along with merchandise offerings, to help promote love for our titles so they become part of the conversation zeitgeist for longer periods of time and drive long-term value for Netflix.

Data is a crucial component in shaping our comprehensive conversation strategy. In Content & Conversation Applied Science and Analytics (CASAS) DSE, we focus on delivering data products and insights that support our business partners in their complex and nuanced decision-making processes. We are a highly collaborative team that partners across Netflix to drive impact.

We are seeking a talented Data Scientist to provide key insights and thought partnership to our Experience team decision makers. You will leverage analytical expertise to build advanced analytical models, develop insights, and uncover trends for Netflix House locations (visitation, attendance, fan behavior, and satisfaction). Your work will directly inform executive decision making as well as optimization and re-forecasting processes in order to enhance fan and House employee experience. In success, you will collaborate on existing priorities but also will propose and execute on new opportunities. This role features ample opportunity for project ownership, leadership and direct influence on impactful business decisions. 

In this role, you will:

• Be a strategic thought partner with business stakeholders to define high impact analytical problems and innovative ways to solve them with data.

• Develop systems to analyze trends in fan behavior, including time spent, arrival and departure patterns, interactions with different Netflix IPs and spaces, and preferences for retail and F&B offerings.

• Develop robust forecasting models to identify future trends, explaining attendance due to seasonality, location, price demand relationship, and other key influencing factors and enabling the business to make data-driven decisions and proactively adapt strategies based on actionable insights.

• Act as a trusted advisor to business leaders, directly informing decision-making and operational planning.

• Actively identify emerging business needs and develop analytical tools to translate outputs to actionable, recommendations for operations teams.

• Present findings and recommendations to stakeholders through clear, compelling story telling and presentations.

• Stay current with industry best practices and emerging analytics trends to continuously improve analytics capabilities.

• Promote and foster a mindset of continuous innovation for internal teams and external partners.

What you’ll bring:

• Exceptional interpersonal and communication skills to influence stakeholders using clear insights and recommendations.

• Adept at cultivating strong partnerships.

• Exceptional thought partnership and engagement abilities with a diverse set of stakeholders and passionate about communicating difficult concepts to non-technical audiences.

• Experience with guest or customer satisfaction analytics, forecasting, and operational optimization is highly desirable.

• Strong statistical knowledge: understanding of predictive modeling; experience in feature engineering, confounder identification and amelioration, etc.

• A degree in a quantitative field (e.g., mathematics, statistics, computer science, engineering, or similar), and 4+ years of experience in data science, analytics engineering, or a similar data field.

• Advanced SQL skills, with experience working in complex data environments.

• Experience with scripting languages, particularly Python.

• Exceptional analytical and problem-solving skills with a keen attention to detail and desire to think outside the box and innovate

• Experience with data visualization platforms (e.g., Tableau, Looker, Plotly) is a plus 

• Experience in  retail, entertainment, or hospitality sectors is a plus.

• Enthusiastic about Netflix culture.

Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here.

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.