Data Optimization Specialist

4 days ago

Mountain View, California, United States BetterHelp Full time

BetterHelp is dedicated to revolutionizing mental health care by making it more accessible and affordable. With a global presence in over 210 countries and more than 60 languages, we've helped millions of people take control of their mental well-being. Our mission is ongoing, as we strive to address the ever-growing need for mental health services.

As a Data Scientist at BetterHelp, you'll become part of a diverse team of professionals who are passionate about expanding access to therapy. We prioritize our employees' mental health and well-being, recognizing that personal growth and professional development go hand-in-hand. At BetterHelp, you'll have the freedom to shape your own path, make a tangible impact, and be challenged daily – all while having the support of a collaborative community.

What are we looking for?

We're seeking a highly skilled Data Scientist to help us scale our impact and optimize our marketing efforts. You will leverage cutting-edge methodologies to drive data-driven decision-making. The ideal candidate has experience working with large and complex datasets related to web products. Your contributions will focus on marketing inference, including our Marketing Mix Model and Attribution.

What will you do?
  • Draw valuable insights from vast amounts of data, collaborating closely with the marketing team to identify and test data-driven strategies for enhancing efficiency.
  • Contribute to the development, implementation, and maintenance of our marketing models, encompassing a Bayesian Marketing Mix Model and a Data-Driven Attribution model.
  • Analyze marketing uplift tests with statistical rigor, present findings to the team, and drive marketing decisions.
  • Address complex problems by proposing testable models and algorithms with measurable business impact.
  • Foster great teamwork, enjoy the process, and take pride in crafting a world-class product that makes a profound difference in people's lives.
What won't you do?
  • You won't worry about financial constraints or time-sensitive pressures.
  • You won't be confined to your job role; instead, you'll contribute to various aspects of our operations, including product development, marketing, business strategy, and more.
  • You won't be hindered by office politics, ego clashes, or negative attitudes; our team thrives on positivity and collaboration.
  • You won't burn out due to excessive work demands; we prioritize maintaining a healthy work-life balance.
Requirements
  • Bachelor's or Master's degree in a quantitative field such as Statistics, Math, Economics, Computer Science, Operations Research, or Engineering.
  • At least 3-5 years of experience in a quantitative data analysis role involving user behavior (e.g., marketing, product, UI/UX) and large datasets.
  • Expertise in statistics, particularly hypothesis testing and experiment design.
  • Experience analyzing A/B tests and experiments using advanced statistical methods like difference-in-difference, regression discontinuity, or other techniques addressing network effects or panel data.
  • Experience building predictive models and causal inference models.
  • Proficiency in analyzing large and complex datasets to drive business insights and decisions.
  • Strong skills in utilizing tools like R and Python for data analysis.
  • Proven track record of supporting or driving business decisions based on data analysis.
  • Excellent communication skills, with experience simplifying complex topics and conveying technical ideas to non-technical audiences.
  • Advanced experience with SQL.

The estimated salary range for this position is $110,000 - $150,000 per year, plus performance-based bonuses and an array of benefits listed below (subject to eligibility requirements).

We celebrate individuality and diversity at BetterHelp and are proud to be an Equal Opportunity Employer. We never 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.

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