Data Scientist, Experimentation and Causal Inference

Data Scientist, Experimentation and Causal Inference

Hearst Newspapers is looking for a Data Scientist to join our Business Intelligence team. Reporting to the Director of Business Intelligence, this role will work as part of a high impact, high throughput division on experimentation and causal inference, serving the organization across product, marketing, subscriptions, advertising, and editorial.

On the Business Intelligence team, you will be the leading subject matter expert on experimentation and causal inference, and a critical resource regarding analyses that require statistical rigor or advanced techniques.

Across the greater organization, you will work directly with non-technical business stakeholders to translate questions concerning key business decisions into statistical problems. In that capacity, you will determine the correct statistical framework for answering the question, work with your stakeholders to ensure data requirements are communicated and experimental design requirements are met, perform the statistical analysis, and ultimately present your findings in an easily digestible and human friendly manner to your stakeholders.

Your work will drive the business in developing standards around experimentation, the adoption of causal inference techniques, and the continued evolution towards a more rigorous data-driven decision making process.

Qualifications

• Degree in statistics, econometrics, data science or related quantitative field.
• 2+ years work experience with experimentation and causal inference in a business setting.
• Proficiency with experimentation and causal inference methods (A/B testing, quasi-experimental designs, econometric methods, structural models, matching)
• Proficiency with frequentist and Bayesian methods for experimentation (AB testing, hypothesis testing)
• Strong proficiency in Python or R.
• Strong proficiency in SQL.
• Demonstrated verbal and written communication skills, especially with non-technical audiences.
• Comfortable working independently and autonomously.
• Track record of completing data science projects end to end, from design, implementation validation, to analysis and presentation.
• Experience collaborating with data analysts and data engineers.
• Experience with cloud platforms (Google Cloud Platform preferred)
• Experience with web analytics (e.g. Google Analytics data), transactional data, subscription data (churn and retention, and/or advertising data a plus.
• Experience working with and presenting to non-technical stakeholders.

Responsibilities

• Lead discussions around effective experimental design for A/B tests and quasi-experimental designs.
• Ensure product and engineering teams have the requirements necessary to implement well designed tests.
• Present findings of experiments and causal inference studies to non-technical stakeholders
• Use causal inference methods to determine the impact of changes when experimental methods are not practical or possible
• Develop and document standards for experimental design and causal inference methods.
• Collaborate with the BI team by providing statistical expertise where necessary.

As part of its continued efforts to maintain a safe workplace for employees, Hearst Newspapers requires that all employees who receive a written offer of employment to be fully vaccinated (as defined by the CDC) against the coronavirus by the first day of employment as a condition of employment, to the extent permitted by applicable law. Hearst Newspapers will consider requests for reasonable accommodations on an individual basis in accordance with applicable legal requirements.