Senior Data Scientist, Attribution
2 weeks ago
Spearhead the effort to architect and build the next-generation, data-driven attribution system for Square. This attribution system is a top priority of Square’s GTM effort to optimize investment and drive growth, and will be based on solid scientific methodology that is defensible and explainable
Build various attribution models as the building blocks for the next-generation attribution system by utilizing techniques such as MTA (multi-touch attribution), MMM (Marketing Mix Modeling), Incrementality test as well as other emerging technologies
Collaborate with MLEs to develop and evaluate advanced MTA by utilizing a combination of first party and third party data
Work with data scientists across a wide organization such as marketing, sales, product to design and evaluate attribution models
Partner with data engineers to evaluate, improve and potentially revamp existing data pipelines to achieve higher data quality, lower latency and be ready for the next-generation attribution system
Take an econometric, holistic view to design and evaluate ROI and marginal ROI metrics that will go hand-in-hand with attribution system to guide Square’s investment to generate best return and fuel growth
Collaborate with cross-functional partners. To name a few: finance, marketing, sales, product, seller lifecycle.
Research and explore cutting edge methodologies, stay up to date with the latest industry trends and best practices
Qualifications
Deep expertise in statistical and machine learning methods for go-to-market attribution and hands-on experience with building end-to-end attribution systems that may include Marketing Mix Modeling (MMM) algorithmic multi-touch attribution (MTA)
6+ years of data science experience
Thorough understanding of economics in go-to-market including but not limited to incrementality, ROI, marginal ROI, elasticity
Expert in variety of go-to-market experimentation techniques
Experience in full-funnel marketing: metrics set up, performance evaluation and optimization
Advanced proficiency in programming languages such as Python, R, SQL
Strong ability to coordinate needs from product, finance, go-to-market to form data and data science strategy and align across the organization
Track record of working effectively and efficiently with product partners to plan, deliver and evaluate martech product
Demonstrated ability to clean and preprocess data using tools like Pandas, NumPy
Proven ability to mentor and coach more junior data scientists
Strong communication skills and ability to collaborate with cross-functional teams and proven record to influence business strategy
Knowledge of the advertising industry and familiarity with ad tech platforms, including future trends due to evolution of the data privacy landscape
Familiarity with classical statistical modeling techniques suitable for small data
Expert in causal inference through both testing and modeling
An advanced degree (M.S. or Ph.D.) in Statistics, Computer Science, Operations Research, or a related technical field
Additional Information
Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.Zone A: USD $184,100 – USD $225,000Zone B: USD $174,900 – USD $213,700Zone C: USD $165,700 – USD $202,500Zone D: USD $156,400 – USD $191,200To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information.Full-time employee benefits include the following:
Healthcare coverage (Medical, Vision and Dental insurance)
Health Savings Account and Flexible Spending Account
Retirement Plans including company match
Employee Stock Purchase Program
Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance
Paid parental and caregiving leave
Paid time off (including 12 paid holidays)
Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees)
Learning and Development resources
Paid Life insurance, AD&D, and disability benefits
Additional Perks such as WFH reimbursements and free access to caregiving, legal, and discounted resources
These benefits are further detailed in Block’s policies. This role is also eligible to participate in Block’s equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.
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