BlueChip Financial is looking for an entry-level ML data scientist to join our cutting edge team of analysts and engineers to expand our internal machine learning solutions. BlueChip continues to demonstrate rapid growth and increasing profit, yet our tech team is relatively small. We have a start-up-like mentality and atmosphere. We're a team of really sharp people in a work environment that is fun, challenging, and rewarding. The focus of the work you'd be involved in is directly tied to the optimization of our machine learning/AI automation infrastructure , with a particular focus upon model performance evaluation and business impact. The compensation (base + bonus) and benefits package for this position is highly competitive. Our working environment is both casual and inclusive. BlueChip Financials primary technology team is located in Atlanta, Georgia, however, fully remote work is an option.
As a Data Scientist I at BlueChip Financial, your primary responsibilities will be to:
- Contribute to specific data science projects and production ML pipelines (e.g., exploratory analysis, production ETL, code test/review, etc.)
- Utilize and help to improve our Machine Learning pipelines for our loan underwriting platform, fraud prevention, marketing, and more...
- Work both independently and as part of a team to solve problems and accomplish tasks in a logical, methodical, and time-efficient manner when given high-level tasks or objectives.
- Build and maintain ML specific dashboards and performance monitoring utilities
- Develop and integrate analytical methods for quantifying/optimizing model performance (e.g., cutoff/threshold optimization)
- Ad Hoc Analyses
- 0-2 years experience in Data Science or related field
- Proficiency in Python and associated data science related dependencies, such as pandas and sklearn. Strong skills in SQL and/or R are a plus.
- Strong mathematical skill and interest in using mathematics daily
- Experience/strong interest in evaluation of ML model performance from a production point-of-view (e.g., threshold assessments of classification/regression model output)
- Experience building, documenting, testing and deploying machine learning pipelines
- Ability to pass a background check.
- Clear and Strong communication skills, desire and ability to collaborate, and no ego
- Strong interest in analysis and finding new insights
- Experience with both larger scale relational and non-relational data frameworks
- Ability and strong interest for learning new things and collaborating well with others
- Baccalaureate (or higher) from an accredited and competitive University in a quantitatively-oriented discipline
- A genuine sense of enjoyment writing code and solving tough problems with data and programming
- Experience in financial services or other highly regulated environments.
- Mathematics/Statistics background is desirable
- The opportunity to help bring much-needed income and economic development to the Turtle Mountain Band of Chippewa Indians
- Competitive salary and performance bonus
- Robust healthcare plans, matching 401K, internet and cell phone line and data reimbursement and four weeks of PTO
- Company sponsored travel to conferences for professional development and training opportunities
About the Company
BlueChip Financial (d/b/a Spotloan.com) is a leading online direct lender founded in 2012 that utilizes advanced underwriting technology to provide short-term loans to Americans in need. BCF is wholly owned and operated by the Turtle Mountain Band of Chippewa Indians of North Dakota, a Federally-recognized Native American Tribe (the "Tribe").
BlueChip Financial is an integral part of the Tribe's economic development efforts, and it is an essential provider of employment opportunities on the Tribe's reservation. Employment decisions at BCF are based on qualifications, ability, and merit. When qualifications are equal, candidates who are enrolled members of the Tribe will receive preference. After considering this preference, it is BCF's policy to provide equal employment opportunity to all qualified persons without regard to race, color, religion, sexual orientation, age, disability, or national origin.