The Data Scientist’s primary role is to explore, build, and deploy proprietary data assets using data science techniques. This role involves working directly with business users to define and manage our machine learning strategy and AI-driven product enhancements. The Data Scientist is responsible for building new data assets in our machine learning pipeline and monitoring the performance of our infrastructure. The role also involves managing advanced data analysis projects and applying advanced statistics and algorithms to answer key business questions. The Data Scientist should have a good understanding of statistics, predictive models, natural language algorithms, python or R, SQL, and AWS.
- Design and build predictive models and natural language processing algorithms.
- Monitor the performance of machine learning assets and identify improvements.
- Manage our machine learning infrastructure to ensure data accuracy and timeliness.
- Identify and test new algorithms and innovative uses of machine learning to solve business problems.
- Develop and support internal python packages.
Data Management and Analysis
- Apply data science techniques to answer complex business questions.
- Design and build statistically reliable test plans to improve product performance.
- Discover and evaluate new data assets to build from existing or third-party data sources.
- Write advanced SQL and build ad hoc datasets to support projects.
- Recommend and implement processes to improve data quality and reliability of analysis projects.
- Build and manage the roadmap for all data science projects.
- Define requirements for all data science projects based on interactions with internal and external stakeholders.
- Summarize the results from machine learning and analysis projects.
- Explain data science findings and model results to business stakeholders in a clear, concise way.
Required Skills and Experience:
- BS, MS, or PhD in math, statistics or anlaytics related field.
- 2-5 years experience in Python or R.
- 2+ years working on data science problems.
- Experience building, evaluating, and presenting machine learning models and their findings.
- Experience with AWS.
- Experience deploying machine learning models in a production environment.
- Strong statistics and SQL knowledge.
- Familiarity with Jupyter notebooks as well as distributed compute technologies like Hadoop and Spark preferred.
- Proven ability to go beyond project-specific work, be innovative, and bring new ideas to the table to improve the overall data and analytics process.
- Strong project management skills with a relentless attention to detail and accuracy.
- Strong problem-solver and strategic thinker.
Job Benefits & Perks:
- Paid health, dental, and vision insurance.
- 401K, paid holidays, and PTO.
- Competitive wage; compensation commensurate with skills and experience.
- Weekly yoga and in-house massage therapist.
- Discount on recreation organizations.
- Downtown Clearwater parking.
- Annual parties and social events.