Tala is hiring a

Senior Data Scientist, Causal Inference

Full-Time
Remote
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.

  • Preferred Skills & Experience:
  • Experience deploying real-time model inference/scoring systems

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