Staff Data Scientist

The Role

We’re looking for a technical and skilled Staff Data Scientist to play a lead role in the Member Data Scientist team, responsible for driving Growth, Engagement, and Retention strategies. The Member Organization is the connective tissue at SoFi, we are dedicated to understanding our members and their behaviors to help them achieve financial independence and reach their goals.

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 help 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

• Identify high impact business opportunities to help members achieve their financial goals
• Mentor and guide data scientists in the team by promoting best practices, strong technical decisions, coding standards, and thorough documentation.
• Develop and apply machine learning models to solve business problems
• Evaluate and interpret the results of data analysis
• Build strong relationships with stakeholders and present insights on a regular cadence communicating findings to both technical and non-technical stakeholders.
• Design and implement data collection. Build data pipelines to deploy production level datasets.
• Collaborate with cross-functional teams and business leader to understand needs and offer data-driven solutions
• Participate in internal team Knowledge sharing session and willingness to mentor junior Data Scientists in the team
• Stay up-to-date on the latest data science techniques and technologies

What You’ll Need

• Masters’ or above in quantitative areas: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years of relevant experience leveraging data-driven analysis to influence key decisions, preferably in a tech company
• Proven track record of being able to work independently, and proactively engaging with business stakeholders with minimal direction and drive measurable business impact.
• Advanced skill set in crafting clean, efficient, and scalable code that adheres to industry best practices, including utilization of version control systems like Git.
• Strong understanding of data mining, machine learning, and statistical modeling.  
• Conduct A/B testing and other experiments to validate the effectiveness of data models
• Knowledge of varied ML algorithms, applicability to different business problems, and experience in deploying ML models at scale in production with monitoring metrics.
• Identify quasi-experimental opportunities, conduct relevant analyses, communicate results effectively, and collaborate with stakeholders to turn findings into actions
• Be proficient with SQL, Python (or any other coding language), and visualization tools
• Experience with using DBT to set up ELT/data pipelines, automate jobs via Airflow 
• Ability to provide data insights for 0-1 products, comfortable with driving the direction of the roadmap for a data strategy. 
• Excellent communication and presentation skills, able to create dashboards to deliver insights 
• Ability to cross collaborate, work in an ambiguous environment with strong problem-solving skills, and mentor junior data scientists