Senior Data Scientist, Causal Inference
Tala
Data Science
Remote · United States
Posted on Tuesday, April 23, 2024
We are looking for a Senior Data Scientist interested in solving one of the world's biggest problems: financial inclusion. As a Data Scientist, you will lead data science initiatives that drive improvements in customer experience, operational efficiency, and recovery. You will own the modeling cycle through scoping, development, deployment, after-sale, and monitoring, with a keen focus on business outcomes and stakeholder management.
What You'll Do
- Embed with business stakeholders to identify, test, and implement data science solutions with a particular focus on econometric models, experiments, and frameworks to assess challenging causal problems such as lifetime value or retention.
- Develop a roadmap in collaboration with stakeholders to organize and prioritize initiatives.
- Own full-cycle of machine learning products from ideation and training through deployment into our production environment – including real-time inference – and after-sale service. Obsess over machine learning products, deploying and iterating rapidly when necessary.
- Propose, design, and analyze large-scale online experiments and support business stakeholders with experimental design best practices.
- Become a multiplier for the data science team by sharing work, providing mentorship to junior team members, providing technical feedback, and developing work into shared team tooling.
- Be a thought partner for the business, leverage data insights and strong communication skills to influence company strategy. Develop roadmaps in collaboration with stakeholders to organize and prioritize initiatives.
What You'll Need
- 4+ years of experience in a data science role or equivalent position.
- You have 2+ years of experience in a senior/lead position, leading the execution of end-to-end machine learning solutions for business stakeholders.
- Fluency with Python and packages related to machine learning.
- Comfort with SQL.
- Experience with the full modeling cycle, from scoping and development through deployment, after-sale, and monitoring. Demonstrated delivery of business value in previous roles.
- Competency with statistics. Knowledge of experimental design and analysis. Previous experience with causal modeling techniques.
- Strong collaboration and communication skills. Ability to tell stories through data and effective visualization.
- Ability to thrive in, at times, ambiguous and complex environments.
- Desire to champion simple, robust systems and to deploy and iterate as needed.
- Experience deploying real-time model inference/scoring systems
Preferred Skills & Experience: