Staff Data Scientist, Borrow

The role

The Borrow Data Science team is seeking a Staff Data Scientist who will help support growth in our Personal Loans business by improving SoFi’s ability to execute with data.  This is an exciting role for someone to leverage their analytical skills to create robust reporting, identify growth opportunities and insights, and build ML models using Snowflake, Airflow, dbt, and Sagemaker.

As a Staff Data Scientist, you will serve as a data leader, balancing urgent requests, and delivering high quality projects to key stakeholders, through a clear and repeatable data informed approach. You will be a technical leader, helping the team build reliable, efficient, and scalable data foundations. You will create a culture of strong technical ownership, documenting your approach and ideas to socialize, resulting in strategies that have a wide impact within the organization. You will perform analytical deep-dives to proactively identify most impactful opportunities, and inform future experimentation design and product roadmaps. 

In this role, you'll use your expertise in data analysis, statistical modeling, and machine learning to uncover insights that will directly influence product strategy and revenue growth. This role demands a strong technical foundation (SQL, Python/R, Tableau, Statistics), a deep understanding of business metrics, A/B testing, causal inference analysis, and exceptional collaboration skills.

Additionally, you are expected to work cross-functionally, including: engineering, product managers, lifecycle marketing, data science, design, operations, finance, risk, legal, compliance, and executive teams to set business objectives, define product strategy, prioritize features, and execute on them.

What you’ll do:

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  Identify high impact business opportunities to help members achieve their financial goals

  
  


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  Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation.

  
  


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  Develop and apply machine learning models to solve business problems

  
  


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  Evaluate and interpret the results of data analysis

  
  


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  Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and non-technical stakeholders.

  
  


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  Design and implement data collection. Build data pipelines to deploy production level datasets.

  
  


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  Collaborate with cross-functional teams and business leaders to understand needs and offer data-driven solutions

  
  


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  Act as a technical leader by mentoring and supporting the growth of less experienced team members

  
  

What you’ll need:

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  Masters’ or above in quantitative areas: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field

  
  


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  7+ years of relevant experience leveraging data-driven analysis to influence key decisions, preferably in a Tech or Finance company

  
  


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  Proven track record of being able to work independently, and proactively engaging with business stakeholders with minimal direction and drive measurable business impact.

  
  


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  Experience with using Airflow and DBT to build Data Pipelines in Snowflake

  
  


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  Strong programming skills in SQL and Python

  
  


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  Experience with building data visualizations with Tableau, Looker or other BI tools

  
  


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  Knowledge of varied ML algorithms, applicability to different business problems, and experience in deploying ML models at scale in production with monitoring metrics.

  
  


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  Ability to work in a dynamic, cross-functional environment, with a strong attention to detail;

  
  


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  Effective communication and presentation skills and ability to explain complex analyses in simple terms to business leaders;

  
  


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  Strong relationship building and collaborative skills;

  
  


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  Exceptional problem-solving