Data Scientist II
As a Data Scientist, you will report to the Data Science Manager. You will play a pivotal role in our data-driven decision-making and drive impact for our Growth, Risk, Product, and Marketing teams. You will have the opportunity to work on cutting-edge projects that involve risk modeling, causal inference from experimental results, pricing optimization, and strategy.
What you’ll do:
Depending on the project, you would:
Conduct experimentation and execute causal inference analyses on pricing, marketing, and conversion models to drive revenue optimization.
Develop Pricing Optimization algorithms to maximize the unit economics of our lending products while driving meaningful growth in our origination businesses.
Develop and maintain predictive ML models to assess potential risks and opportunities across our lending products, contributing to the enhancement of risk and marketing assessment procedures.
Conceptualize, research, and prototype data-driven solutions, effectively communicating their impact to the stakeholders.
Collaborate closely with cross-functional teams and stakeholders to accelerate solution iteration and achieve measurable outcomes.
Build funnel dashboards and perform root cause analysis to monitor and identify user behavioral patterns and areas of opportunity.
Collaborate with data and infrastructure engineers to deploy ML and Pricing pipelines, from data collection through model deployment. This includes automating training and ongoing monitoring utilizing BI tools.
Prepare technical designs and documentation using git and Confluence.
Ideal background and expertise:
2+ years of experience in R/Python and SQL
2+ years professional experience in model development and/or data analytics (or Master's degree in Data Science, Operations Research, Industrial Engineering, Economics or a related quantitative field with 1+ years of professional experience in model development and analytics)
Expertise in statistical inference.
Experience in product analytics and experimental design.
Expertise in building classification, regression, and forecasting models and deriving insights from A/B tests.
Experience working in a cross-functional environment with teamwork and excellent communication skills.
Bonus to have:
Understanding of financial metrics and bond markets.
Understanding of econometrics and elasticity in pricing optimization.
Previous experience with cloud platforms such as AWS, Azure, or GCP.
Experience with BI stack such as Looker, Airflow, and DBT.
Custom LLM and NLP experience.
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About the job
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Data Scientist II
As a Data Scientist, you will report to the Data Science Manager. You will play a pivotal role in our data-driven decision-making and drive impact for our Growth, Risk, Product, and Marketing teams. You will have the opportunity to work on cutting-edge projects that involve risk modeling, causal inference from experimental results, pricing optimization, and strategy.
What you’ll do:
Depending on the project, you would:
Conduct experimentation and execute causal inference analyses on pricing, marketing, and conversion models to drive revenue optimization.
Develop Pricing Optimization algorithms to maximize the unit economics of our lending products while driving meaningful growth in our origination businesses.
Develop and maintain predictive ML models to assess potential risks and opportunities across our lending products, contributing to the enhancement of risk and marketing assessment procedures.
Conceptualize, research, and prototype data-driven solutions, effectively communicating their impact to the stakeholders.
Collaborate closely with cross-functional teams and stakeholders to accelerate solution iteration and achieve measurable outcomes.
Build funnel dashboards and perform root cause analysis to monitor and identify user behavioral patterns and areas of opportunity.
Collaborate with data and infrastructure engineers to deploy ML and Pricing pipelines, from data collection through model deployment. This includes automating training and ongoing monitoring utilizing BI tools.
Prepare technical designs and documentation using git and Confluence.
Ideal background and expertise:
2+ years of experience in R/Python and SQL
2+ years professional experience in model development and/or data analytics (or Master's degree in Data Science, Operations Research, Industrial Engineering, Economics or a related quantitative field with 1+ years of professional experience in model development and analytics)
Expertise in statistical inference.
Experience in product analytics and experimental design.
Expertise in building classification, regression, and forecasting models and deriving insights from A/B tests.
Experience working in a cross-functional environment with teamwork and excellent communication skills.
Bonus to have:
Understanding of financial metrics and bond markets.
Understanding of econometrics and elasticity in pricing optimization.
Previous experience with cloud platforms such as AWS, Azure, or GCP.
Experience with BI stack such as Looker, Airflow, and DBT.
Custom LLM and NLP experience.
#LI-