Full-Time Lead Data Scientist

As Lead Data Scientist at Apollo, you’ll be the pioneer in setting up our Data Science practice, being the first on the team. You’ll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. You’ll build the systems that ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. You have the technical excellence, leadership skills, and a track record of impactful work.

Who you are

You care deeply about working effectively across cross-functional teams to land outcomes. You’re fundamentally excited to be a part of building the infrastructure of the future. You have an insatiable curiosity, humility, and drive to hone your craft. You lead with a growth mindset – the work is never done and there’s something to learn from everyone. We highly encourage you to apply if you meet these minimum requirements.

About the role

• [Domain] Deep expertise in building the right systems for data analysis, modeling, visualization and prediction, to land optimal business outcomes.
• [Technical Leadership] Expert problem solver, able to balance technical requirements, with human elements, business constraints, and broader project context, to effectively drive trade-offs amidst high ambiguity. Assume hands-on leadership, especially when helping teams set their long-term vision and resolve complex problems through iterative execution.
• [Project management]: Proficient in planning projects, managing requirements across key stakeholders, and ensuring ethical data practices. 
• [Collaboration]: Working with the executive team, and key cross-functional stakeholders to identify opportunities and implement models to influence the org effectively. 
• [Communication]: Presenting findings to stakeholders and communicating complex insights to non-technical audiences.

Minimum requirements

• ~10 years of data science/quantitative modeling experience to solve business and product problems; proficiency in SQL and a computing language such as Python or R
• Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
• Demonstrated experience of leading organization-wide initiatives spanning multiple teams, or leveraging deep domain and business expertise to influence tech roadmap planning and execution
• Ability to communicate results clearly with a focus on driving impact
• Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes
• Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
• A builder's mindset with a willingness to question assumptions and conventional wisdom
• May be required to participate in on-call rotation

Preferred Qualifications

• Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
• Experience working in Growth on problems like attribution, channel performance optimization, CAC optimization and experimentation.
• Experience with distributed tools such as Spark, Hadoop, etc.
• A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)Experience developing and deploying metric frameworks