The Decision Science team drives data-driven strategy and decision making across the company through predictive analytics, testing and optimization. We work on a wide variety of problems. We drive product prioritization and inform business strategy by developing a deep understanding of our users and clients. We work with Product team to build and refine data products, such as personalization to power the site and internal products, such as fraud detection, to improve our business efficiencies. We work with Sales team to score and prioritize leads, with Marketing team to build media models, optimize spend to increase pipeline, with Marketplace to understand elasticity of supply and demand, and work with Finance and Business Operations teams on financial planning and forecasting. If gaining exposure to a wide variety of business functions across a fast-growing company excites you, this is the place to be.
Our product philosophy is to build products that solve user pains. We are relentless in learning through experimentation. Since different job seekers have different needs, every feature we build must be contextual and personalized. Data informs every feature we build. We deeply analyze user behavior, through our logs or external research.
The Lead Data Analyst will be working with a number of internal teams including Employer Marketing, Sales, Marketplace, and Employer Product. This person will initially be an individual contributor with the possibility of 1-2 direct report.
A typical week would comprise of brainstorming with stakeholders on new project ideas, building strategy and criteria for success of the project, KPI measurement, building dashboards for business teams to consume, analyzing the health of our product, developing insights and recommendations based on deep dive analyses.
A sampling of projects –
Evaluate relationship between applicant delivery and business outcomes and segment by customer type, job type etc. Provide deeper insight into who our Self-Service customers are and to improve retention. Understand Employer Enhanced Profile penetration and engagement. How does Employer Center engagement lead to business outcomes and retention?
The ideal candidate will be extremely results driven and passionate about winning. You exercise very sound judgment and have the ability to balance sophistication with simplicity, scientific rigor with pragmatism and agility with quality.
4+ years of quantitative experience, ideally in an Internet company. Quantitative Degree – like Statistics, Operations Research, Physics, Computer Science, Economics, etc.
Leadership: Ability to partner with executives, business stakeholders and product managers to define roadmaps. You see what could be and drive the organization there.
Strong applied analytics: This means you love data, gleaning insights from data, and making decisions based on data. You need to have demonstrable history of doing this.
Outstanding problem solving skills: You’re not just repeating a playbook, you’re looking at every problem with fresh eyes and digging deep for insights and solutions.
Experience with techniques and tools: Hands-on experience working with large data-sets, modeling, and statistics. Proficiency at SQL, R or Python. Extensive A/B & multivariate testing experience.