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Senior Data Scientist - Machine Learning

Austin

Self Financial is a venture-backed, high-growth FinTech company with a mission to increase economic inclusion and financial resilience by empowering people to build credit and build savings.

We're looking for people who share our passion and are driven to tackle challenges, find solutions and make the financial space better for the communities we serve.

Our team is passionate about challenging the status quo of the credit industry by providing people accessible tools to take control of their credit. Executing on our mission requires deep collaboration across our teams to ensure our products reach the people who can benefit from them the most, particularly the 100 million+ Americans who have no or low credit.

We celebrate diversity and are committed to creating an inclusive environment for all employees. To that end, we seek to recruit, develop and retain the most talented people from a diverse candidate pool.

Position Overview

We are seeking a highly skilled and motivated Data Scientist with expertise in building machine learning models, deploying models, and creating pipelines. The ideal candidate will have extensive experience with AWS Machine Learning cloud tools and a strong background in data analysis, statistical modeling, and software engineering. This role requires a blend of technical proficiency, creativity, and the ability to work collaboratively in a fast-paced environment.

What You’ll Do:

  • Develop Machine Learning Models: Design, build, and refine machine learning models for various applications, ensuring high accuracy, efficiency, and scalability.
  • Model Deployment: Deploy machine learning models in production environments using AWS ML tools, ensuring models are robust, reliable, and maintainable.
  • Pipeline Creation: Develop and maintain data pipelines that preprocess, transform, and ensure the integrity of data for model training and prediction.
  • Data Analysis and Visualization: Conduct thorough data analysis to extract meaningful insights and visualize data to support decision-making processes.
  • Collaborate with Cross-Functional Teams: Work closely with data engineers, software developers, product managers, and other stakeholders to integrate ML models into applications and workflows.
  • Stay Current with Industry Trends: Keep abreast of the latest advancements in machine learning, data science, and AWS technologies to continuously improve skills and apply best practices.
  • Documentation and Reporting: Document methodologies, processes, and results comprehensively. Present findings and insights to technical and non-technical stakeholders.

What we want you to have:

  • Masters or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field
  • Proficiency in programming languages such as Python, R, and SQL.
  • Strong understanding of machine learning algorithms, statistical models, and data structures.
  • Experience with AWS Machine Learning services, including but not limited to SageMaker, Lambda, Glue, and Redshift.
  • Expertise in deploying models in a cloud environment and managing end-to-end ML pipelines.
  • Familiarity with frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, and Pandas.

   Experience:

  • Minimum of 7- 10 years of hands-on experience in building, deploying, and maintaining machine learning models in production.
  • Proven track record of working with large datasets and implementing data preprocessing, feature engineering, and model evaluation techniques.
  • Experience with DevOps practices and tools for continuous integration/continuous deployment (CI/CD) is a plus.

   Soft Skills:

  • Strong problem-solving skills and the ability to work independently as well as part of a team.
  • Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders.
  • High attention to detail and a passion for delivering high-quality work.

 

Base salary range: $180,000- $210,000 annually.  Individual pay is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.

Benefits and Perks:

We have the compensation and benefits you expect. But there's one thing that Self Financial can offer that many companies cannot: we can positively change the world, while making a profit. We are a team of Builders, empowering our customers to build their dreams. We have a Do the Right Thing ethos in all that we do, and we hope you value that approach, too. 

Our perks include:

  • Company Equity in the form of Stock Options
  • Quarterly performance-based bonuses
  • Generous employer-paid health, vision and dental insurance coverage
  • Flexible vacation policy
  • Educational assistance
  • Free gym membership
  • Casual dress code
  • Team building events and activities
  • Remote work arrangements/ flexible work schedule
  • Paid parental leave 

Self Financial requires all employees hired to successfully pass a background check.

We are an Equal Opportunity Employer.

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