Senior Data Scientist - AI/ML Solutions

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