Your Job
As a Senior Data Scientist - AI/ML Solutions, you will join our client's team of Data Scientists to develop advanced data science solutions using machine learning and artificial intelligence. Your role will involve leading use case/workstream with junior data scientists and supporting use case development from initial data exploration to the creation of final reports. You will utilize advanced statistical and AI/ML techniques to create predictive models and analyses that address business objectives. Additionally, you will collaborate with cross-functional teams, perform data wrangling and ETL, and ensure data accuracy and consistent reporting. This is an exciting opportunity to apply cutting-edge technology and contribute to our client's ongoing evolution as a forward-thinking insurance company.
The Work
- Lead use case/workstream with junior data scientists
- Support use case development including data exploration, project/sample design, data reception and processing, analysis and modeling, and creation of final report/presentation
- Perform data wrangling/data matching/ETL to explore various data sources, gain data expertise, perform summary analyses, and prepare modeling datasets
- Utilize advanced statistical and AI/ML techniques to create high-performing predictive models and creative analyses to address business objectives and partner needs
- Identify source data and perform data quality checks both in model/solution development and in production
- Package model/solution and deploy it in cooperation with Data Engineers and MLOps
- Implement new statistical or other mathematical methodologies as needed for specific models or analysis.
Qualifications
Meets one of the following Education AND Experience combinations:
- Combination 1 - PhD with 2+ years of experience
or
- Combination 2 - Master's degree with 4+ years of experience in Statistics, Computer Science, Engineering, Applied mathematics or related field
- 3+ years of hands-on ML modeling/development experience
- Solid understanding of data analysis and statistical modeling
- Knowledge of a variety of machine learning techniques and their real-world advantages/drawbacks
- Demonstrated track record in experimental design and execution
- Hands-on experience with data wrangling including fuzzy matching and regular expression, distributed computing, and applying parallelism to ML solutions
- Strong programming skills in Python
- Solid background in algorithms and a range of ML models
- Excellent communication skills and ability to work and collaborate cross-functionally with Product, Engineering, and other disciplines at both the leadership and hands-on level
- Excellent analytical and problem-solving abilities with superb attention to detail
- Proven leadership in providing technical leadership and mentoring to data scientists, strong management skills with the ability to monitor/track performance for enterprise success
Nice to Have
- Experience with deep learning and neural networks
- Familiarity with big data technologies such as Hadoop and Spark
- Knowledge of natural language processing (NLP) techniques
- Understanding of cloud computing platforms such as AWS or Azure
- Previous experience in the insurance or financial industry