Snap Finance
Staff Machine Learning Engineer
Job Description
Are you looking for a friendly, fast-paced workplace with an emphasis on helping customers and empowering team members? Snap Finance is a thriving leader in the financial services industry, and our team members are the foundation of our success. Snap knows that happy, empowered, and engaged team members are essential to innovation and business success- and our approach is working. Come join us!
Job Description
We are looking for a staff level machine learning engineer to join our machine learning team. The ideal person will have significant industry experience working on a range of classification and optimization problems. This person will take their expertise and apply it to exciting and diverse multimodal data with some of the most interesting and challenging inference problems in machine learning. They will be able to define new frameworks, tools, or processes that improve the overall engineering productivity and quality. Position would include model development and deployment and compiling/analyzing data from multiple sources with the objective of improving predictions to reduce risk, empower consumers and broaden our influence in a rapidly growing market of alternative finance.
Key Responsibilities:
- Develop and innovate on state-of-the-art, scalable models and tools leveraging artificial intelligence, machine learning, optimization, and rules-based models.
- Push the boundaries of what’s possible for assessing creditworthiness optimizing risk and analyzing customer behavior
- Propose, gather and integrate data and create valuable features
- Code projects in parallel with the data engineering team
- Assemble large, complex data sets that meet functional and non-functional business requirements
Qualifications:
- MS or PhD in a quantitative field such as Statistics, Econometrics, Mathematics, Physics, Computer Science, or related quantitative field.
- Possess broad and deep technical expertise across multiple areas of machine learning. They often
- History of tackling challenging technical problems and involvement in making high-level decisions about technology choices and system architecture.
- BS in the fields described above will be considered if skill set and experience are robust
- 7+ years experience in one or more of the following areas: machine learning, artificial intelligence, recommendation systems, data mining, or related research
Skills, Experience & Qualifications Required
- Strong background in Python, Java , or other general-purpose programming languages
- Extensive experience with deep learning and traditional classification methods (e.g. Neural Networks, Gradient Boosting, Decision Trees, Random Forest)
- Proficiency and working knowledge of at least one major deep learning framework (e.g. PyTorch, TensorFlow)
- Experience with filesystems, server architectures, and distributed systems
- Sequence modeling (e.g.RNNs, Natural Language Processing techniques, Attention-Based Autoregressive models)
- Statistical analysis (e.g., Hypothesis testing, experimental design, hierarchical modeling, Bayesian and Frequentist methods)
- Experience with automated workflows: Airflow, Jenkins, etc.
- Experience with AWS cloud services such as EC2 and S3
- Working knowledge of message queuing, stream processing, and highly scalable data store
- Familiarity with common computing environment (e.g. Linux, Shell Scripting)
- Strong SQL skills
- Proven ability to translate insights into business recommendations
Personal Characteristics:
- Strong analytical and problem solving skills
- Excellent communication skills with the ability to clearly explain technical topics to a non-technical audience
- Team-oriented but able to complete tasks independently at a high standard
- Structured, organized and detail-oriented
- Proactive, enthusiastic and flexible
- Fluency in English, both in oral and written form
- Ability to take projects from conceptualization to implementation
- Must be able to work onsite in our Salt Lake City office and be legal to work in the United States
More…
Snap values diversity and all qualified applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. Learn more by visiting our website at www.snapfinance.com.
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