Role overview
As a full-time Data Scientist at MVP, you will be a part of the growing data science team developing solutions to reshape the way sponsorship marketing is measured, valued and reported to our customers. The Data Scientist role is focused on providing creative and forward-thinking machine learning solutions. While the data science team will be responsible for end-to-end solutions, from ideation and research to development and deployment in platform, your primary focus will be on testing hypotheses, data sleuthing and building innovative proof of concepts. You will develop data pipelines, automated solutions, and machine learning algorithms. You will collaborate with the product, engineering, and customer success teams to develop and execute impactful solutions for our customers.
What you'll work on
- Work with our Client Services teams to streamline processes related to valuation and other data and reporting services to provide actionable data to our customers
- Collaborate with other data scientists, ML engineers, and software engineers to assist in creation of enterprise solutions in a SaaS software distribution environment.
- Research and develop automated solutions for testing and further development. Develop and implement data methodologies, data collection systems, and other strategies that optimize efficiency and quality.
- Contribute to algorithm selection and optimization. Build models and tools using technical knowledge in machine learning, statistical modeling, probability and decision theory, and other quantitative techniques.
- Innovate by learning about and adapting to new techniques and procedures within machine learning, computer vision, etc. Experiment with these techniques for possible inclusion into the production environment.
What we're looking for
- Bachelor’s degree in Computer Science, Statistics, Mathematics or related field
- 2+ years of combined experience in machine learning, statistics, data modeling, programming, or applied research in related fields outside of academia
- Proficiency and experience using Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data
- Strong SQL, database, and ETL skills required including cleaning and managing data.
- Experience working with predictive and statistical modeling, machine learning and experience in all phases of the modeling pipeline
- Ability to work collaboratively with both data scientists and backend engineers
- Familiarity with AWS preferred
- It is a plus if you have experience with, and have Databricks certifications