What you’ll do

• Partner with cross-functional teams to initiate, lead or contribute to large-scale/complex strategic projects, with particular focus on Machine learning initiatives. 
• Work with a team of cross-functional teams to identify new opportunities for business growth and develop algorithms and methodologies to address them.
• Analyze large-scale data and develop and execute rigorous analysis using causal methodology to drive business decisions.
• Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis.
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations and evangelize data-driven business decisions in support of strategic goals.
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.

What we’re looking for

• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data
• Strong background in statistical, machine learning, experimentation
• Proven ability to apply scientific methods to solve real-world problems on web-scale data
• Expertise in at least one scripting language (ideally Python/R)
• Proficiency in SQL/Hive
• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams 
• Experience leading key technical projects and substantially influencing the scope and output of others

What skills are ideal but not required?

Exposure to one or more of the following areas is beneficial. Ideal candidates would have exposure to 2+ of these areas and deep familiarity in 1 or more areas.

• Strongly desired: experience working in Growth function, in particular, experience working on notifications, paid marketing, user acquisition.
• Experience working on ranking algorithms.
• Statistical rigor. Experience with causal inference projects.
• ML modeling, ideally with biased / incomplete training data. Has built models end to end (feature design, feature selection, training data, implementation, iteration, productionization) and can intelligently discuss trade-offs / decisions at each step.

This position is not eligible for relocation assistance.

#LI-NM4 or #LI-REMOTE