Director Analytics Engineering, Corporate Vice President

Key Skills

Aartificial intelligence, Amazon RedShift, Apache Hadoop, AWS, Big Data Technology, Data Analytics, Data pipelines, Data science techniques, Generative AI, Git, Python Programming, Scrum Agile Methodology, Snowflake, SQL

Job Description

The Center for Data Science and Artificial Intelligence (CDSAi) is an innovative corporate Analytics group within New York Life. We are a rapidly growing entrepreneurial department which aims to design, create and offer innovative data-driven solutions for many parts of the enterprise. We are aided by New York Life’s existing business with a large market share in individual life insurance. We have the freedom to explore external data sources and new statistical techniques and are excited about delivering a whole new generation of predictive analytics and artificial intelligence solutions.

In fact, we are building one of the first multivariate model-based continuous risk differentiations in the industry. We are also working on models for differentiated advertising allocation by geography, channel and segment. Geographic analytics on agents and customers, application fraud detection, agent success prediction and client prospecting analytics (off-line and on-line) are other exciting examples of enormous incremental value from analytics. Our products are implemented into real-time core business processes and decisions that drive the company (e.g., underwriting, pricing, agent recruiting, prospecting, advertising allocation, new product development).

We work with data ranging from demographics, credit and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. We have a modern computing environment with a solid suite of data science/modeling tools and packages, and a large (but manageable) group of well-trained professionals at various levels to support you. Life insurance is on the verge of huge change. This is a chance to drive the transformation of an industry.

The Center for Data Science and Artificial Intelligence (CDSAi) is the 60-person innovative corporate Data Science group within New York Life, led by Chief Analytics Officer Glenn Hofmann (https://www.linkedin.com/in/glennhofmann/). We are a rapidly growing entrepreneurial department which designs, creates, and deploys innovative data-driven solutions for many parts of the enterprise. For more opportunities in data science, please visit our website (https://www.newyorklife.com/careers/corporate/data-science)

You will manage and mentor a team of analytics engineers, to provide clean transformed data for data science solutions. You will ensure the team adheres to software and data engineering best-practice standards to create data-pipeline patterns using best-of-breed tools. You'll be an instrumental member of the MLOps team lead by Boris Simanovich (https://www.linkedin.com/in/boris-simanovich/)

Responsibilities

1. Manage and mentor a team of analytics engineers to provide clean transformed data for data science/analytics use cases
2. Establish and maintain best practices to coding formats, naming conventions, and version control
3. Review code changes and approve pull requests (PRs) in Git
4. Convert requirements into Jira stories and provide milestones
5. Partner with data scientists regarding data quality, availability, value, etc.
6. Collaborate with data stewards throughout NYL
7. Build strong relationships with Technology (IT) to work on tooling, data strategy, integrations and deployments
8. Effectively articulate information and ideas to a diverse group of people
9. Stay up to date with the latest Analytics Engineering trends/emerging technologies and look for opportunities to improve the stack

Required qualifications

• 10+ years of industry experience with at least 3-years as a technical hands-on Manager
• Expert in SQL/Python (using dbt or similar tools)
• Experience in automating and managing SQL using software engineering best practices
• Have previously developed standards and practices for data/analytics engineering (architectural data pipeline patterns)
• Experience with big data platforms such as Redshift, Snowflake and Hadoop
• Excellent command of Git
• Experience with cloud compute environments (AWS) along with cloud-native tools
• Experience with Agile/Scrum methodology and best practices
• Graduate-level degree in computer science, engineering, or relevant work experience

Preferred: 

• Previous work experience with Data Science/AI teams
• Exposure to Generative AI and use of unstructured data
• Insurance industry experience