Appied Economist

Ancestry
San Francisco - United States
S: Competitive

We are growing our Marketing Data Science team in San Francisco. We are looking for an applied economist to join and help grow this exciting team.

By joining this team, you will be a member of the global Data Science & Machine Learning Team, tackling our toughest and most exciting data science challenges.

Key Responsibilities

Help the firm make better choices in product innovation, increase customer success, optimize marketing spending, and more across both our family history and consumer genomics businesses
Apply econometric modeling to simplify complex business problems
Grow our profit through development of best-in-class causal inference capabilities: you will be the resident expert on matching methods, regression discontinuity design, instrumental variables and difference-in-differences estimation

Qualifications
Ph.D. in Economics, Applied Economics, or Agricultural Economics, preferably with concentrations in labor, welfare, IO, or a dissertation that makes good use of applied micro-econometrics.
Working experience in the field desired, but we're flexible on what counts (if you did consulting before or during grad school, mention it; if you have a few years post-degree, we are especially interested in what you did; our wish list, our estimate of your reservation wage, and the job title for this position will be adjusted accordingly).
Expertise in statistical computation (in a pinch, you will have to write your own estimators; if you have relevant examples of past work, we would like to see them).
Proven track record of completing multiple estimation projects end to end, from idea generation to objectives formulation to implementation and deliverables.
Fluency in R, Python, Stata or MATLAB required
Fluency in SQL is required
Experience in Scala or Java also a plus
Experience with SPARK would be nice
Excellent written and oral communication skills
Highly skilled at translating business requirements from key stakeholders into work plans

Job summary