Senior Data Scientist, Marketing Inference

Who are we and why should you join us?

BetterHelp is on a mission to remove the traditional barriers to therapy and make mental health care more accessible to everyone. Founded in 2013, we are now the world’s largest online therapy service – providing affordable and convenient therapy in 210 countries and over 60 languages across the globe. Our network of over 30,000 licensed therapists has helped millions of people take ownership of their mental health and change their lives forever. And we’re not stopping there – as the unmet need for mental health services continues to grow, BetterHelp is committed to being part of the solution.

As a Senior Data Scientist at BetterHelp, you’ll join a diverse team of licensed clinicians, engineers, product pros, creatives, marketers, and business leaders who share a passion for expanding access to therapy. And as a mental health company, we take employee mental health just as seriously as we do our mission. We deeply invest in our team’s well-being and professional development, because we know that business and individual growth go hand-in-hand. At BetterHelp, you’ll carve your own path, make an immediate impact, and be challenged every day – with a supportive community behind you the whole way.

What are we looking for?

BetterHelp is looking for a Senior Data Scientist to help us scale and increase our impact. You will use cutting-edge methods to optimize our marketing efforts. The ideal candidate would have experience analyzing large and complex data sets related to web products. You'll be contributing to efforts in marketing inference, including our Marketing Mix Model and Attribution.

What will you do?

• Get insight from an enormous amount of data, and take a proactive role partnering with the marketing team in finding and testing data-driven ideas for improving our efficiency.
• Contribute to the development, implementation, and maintenance of our marketing models, including a Bayesian Marketing Mix Model and a Data-Driven Attribution model.
• Monitor and analyze marketing uplift tests with statistical rigor, present the data and insights to the team, and drive marketing decisions.
• Look at complex problems and come up with testable models and algorithms that have measurable business impact.
• Enjoy great teamwork, have lots of fun, and take pride in building a world-class product that makes a difference in people's lives.

What will you NOT do?

• You will NOT worry about "runway", "cash left", or "how much time we have until the next round". We have the startup DNA but we're fully backed and funded, all the way to success.
• You will NOT be confined to your "job". You will get involved in product, marketing, business strategy, and almost everything we do.
• You will NOT be bogged down by office politics, ego, or bad attitude. Only positive, pleasure-to-work-with people are allowed here!
• You will NOT get yourself burned out. We work hard but we believe in maintaining a sustainable work/life balance. Really.

Can I work remotely?

Yes. We operate on PST and candidates in any time zone are welcome to apply. We ask employees to travel to our Mountain View, CA office up to three times per year plus one company-wide offsite to collaborate in person and strengthen working relationships. Travel expenses are covered and reasonable accommodations are made for those under unique circumstances who cannot travel.

Requirements

• BSc/MA in a quantitative discipline such as Statistics, Math, Economics, Computer Science, Operations Research, or Engineering
• At least 5-8 years of experience in a quantitative data analysis role involving user behavior (e.g. marketing, product, UI/UX) and large data sets
• Expertise in statistics, especially as it relates to hypothesis testing and experiment design
• Experience analyzing A/B tests as well as experiments with more advanced statistical methods like difference-in-difference, regression discontinuity, or other methods that deal with network effects or panel data
• Experience building predictive models and causal inference models
• Experience analyzing large and complex data sets to drive business insights and decisions
• Expertise in using tools like R and Python for data analysis
• Proven success supporting or making business decisions based on your data analysis
• Excellent communication skills, with experience simplifying complex topics and communicating technical ideas with non-technical audiences.
• Advanced experience with SQL

Bonus (Great to have but not required)

• Experience with Bayesian modeling methods
• Experience with Marketing Mix Models and Multi-Touch Attribution models
• Experience analyzing two-sided marketplaces
• Experience with B2C, marketplace products
• Experience with BI tools like Tableau and Looker

Benefits

• Competitive salary & equity compensation
• Excellent health, dental, and vision coverage
• 401k benefits with employer matching contribution
• Unrivaled perks program (including free therapy, UberEats, and more)
• Remote work with regular in-person bonding experiences sponsored by the company
• Office in the heart of downtown Mountain View, a three-minute walk from Caltrain
• Commuter benefits, FSA accounts, and Employee Stock Purchase Programs
• The chance to build something that changes lives – and that people love
• Any piece of hardware or software that will make you happy and productive
• An awesome community of co-workers

The base salary range for this position is $170,000 - $200,000. In addition to the base salary, this position is eligible for a performance bonus and the extensive benefits listed here (subject to eligibility requirements): Teladoc Health Benefits 2025. Total compensation is based on several factors – including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable to all full-time positions.

At BetterHelp we thrive on difference and individuality, and as part of the Teladoc Health family, we are proud to be an Equal Opportunity Employer. We never have and never will discriminate against any job candidate or employee due to age, race, ethnicity, religion, sex, color, national origin, gender, gender identity, sexual orientation, medical condition, marital status, parental status, disability, or Veteran status.