Staff Data Scientist - Ltv

Job Description

Staff Data Scientist - LTV (Life-time Value)

Be part of the Marketing Data Science team within a large organization to support our premium video streaming service HBO Max. The Staff Data Scientist will be responsible for building data science models and advanced analytics tools to help drive growth and improve retention for HBO Max, with specific focus on LTV (Lifetime Value) Predictive Modeling.

The Staff Data Scientist will lead efforts to develop, maintain, and refine data science models to predict customer lifetime value, execute audience segmentation and facilitate forecasting initiatives. You will perform advanced analytics and data mining to help the business understand the HBO Max consumer behavior and retention dynamics You will be working closely with finance, marketing, strategy team and other business stakeholders to drive the impact and decision. You'll be working with a wide array of datasets to craft industry leading models and analyses. Key to this role is the ability to hop into cross-functional projects, executing from start to finish. The Staff Data Scientist aggressively monitors the latest in algorithmic/modeling results and identifies opportunities to apply them impactfully.

The Daily
• Apply supervised and unsupervised machine learning techniques and statistical inferences, such as linear and logistic regression, decision trees, ensemble models, survival model, causal inference, and advanced clustering techniques etc.
• Develop customer lifetime value predictive model, forecasting and propensity models to facilitate customer lifecycle marketing and management. Other projects may include behavioral clustering/segmentation, customer journey analytics etc.
• Lead the development of big data framework and analytical approaches.
• Drive projects at a cross functional level with relevant teams across data engineering, MLE, BI and ensure project success.
• Own the models and how they are used and is responsible for their quality and interpretation from stakeholders, and ensure any SLAs promised are maintained.
• Synthesize analytics and statistical approaches into easy-to-consume storylines, both visually and verbally, and provide indicated actions for executive audiences.
• Capture business requirements for data and analytics solutions and collaborate with the business teams to ensure analytics requirements align with business needs.
• Support day-to-day collaboration with business stakeholders to communicate insights and recommend data informed strategies.
• Conduct innovative modeling research and serve as technical lead on the team.
• Mentor junior Data Scientists.

The Essentials
• BA/BS/MS in quantitative fields such as statistics, mathematics, computer science, engineering, physics, economics, etc. PhD preferred.
• 8+ years of experience building data science models (Time Series, Regression, Decision Trees, Ensemble Models, Clustering, Survival analysis, Deep learning etc.).
• Experience with large data sets and analytical tools (Jupyter notebook, TensorFlow/PyTorch, Scikit-Learn, cloud ML frameworks such as AWS and Apache Airflow).
• Proficiency in programming languages and software development toolkit (advanced SQL, Python, R, C++, Git etc.).
• Knowledge of a dashboarding language (Tableau, Looker, etc.) or equivalent report building experience not required but a plus
Other desired qualifications:
• Strong curiosity, leadership, and business acumen.
• Passionate about using data to drive strategy and product recommendations.
• Experience in subscription-based businesses or eCommerce preferred.
• Strong interpersonal skills with the ability to motivate, collaborate and influence.
• Ability to deliver on multiple projects and meet tight deadlines.
• Ability to adapt rapidly in a fast-moving environment with shifting priorities and the ability to react quickly, dynamically, and intelligently.
• Ability to effectively influence and communicate cross-functionally with all levels, exceptional verbal, and written communication skills.
• Strong presentation skills are a must.

Jobcode: Reference SBJ-rb1y2e-18-118-193-232-42 in your application.