ModelOps Automation Developers - NO C2C - LATAM

Basically, we are looking for someone who can help us with building solutions to support AI Enablement within the organization. Many of these solutions will be built in Databricks using Python as the core language. In addition to Databricks solution (rather than data) and Python development experience, it is preferred the candidates have Snowflake, Jenkins CI/CD, AWS, and Dev Ops experiences.

One example of the type of solutions they will be developing include generalized libraries to support common capabilities data scientists require to develop and deliver solutions on Databricks, such as authentication, authorization, logging, reporting, etc. Another example is automation of a process to create a new model space (RGA term for development environment) which connectivity to a Snowflake schema.

General Summary:

Support RGA business units through the design, implementation, and maintenance of automated workflows and infrastructure to support the machine learning model lifecycle from development to production deployment. Focus is building out robust CI/CD pipelines for ML models, ensuring seamless model versioning, monitoring, and governance while collaborating closely with data scientists and engineering teams. Solutions will leverage cloud platforms and DevOps tools to create scalable, reliable systems that enable efficient model deployment, performance tracking, and automated retraining processes. In addition, emphasis will be on creating best practices for model operations, ensuring compliance with regulatory requirements, and optimizing overall MLOps ecosystem within the organization.

1. Implementation : Assist in the preparation of data sets for use in data science models through the implementation of ingestion and scoring data pipelines. This includes restructuring Python, Scala, and SQL code for API and web access and developing the actual API interface/protocol.
2. Integration : Develop solutions to integrate existing data pipelines and systems with other data sets, systems, and APIs to augment and enhance the data content, supporting statistical and machine learning models in the insurance industry, such as mortality, morbidity, fraud, etc.
3. Data Understanding: When presented with specialist datasets, carry out the full spectrum of data analysis, from the development of statistical analysis plans and design of the database schema, through data cleansing and into the creation of new insights and knowledge based on a thorough and deep statistical analysis of the data;
4. Subject Matter Expertise / Client Contact : Develop subject matter expertise in existing data sets, ingestion and scoring pipelines, system integration and advanced data analytics in insurance applications.
5. Collaboration / Communication : Collaborate with data science, actuarial, and citizen developer teams in support of various data science, advanced analytics and modeling projects. Develop verbal and oral communication skills whenever possible.
6. Perform other duties as required .

Required:

• Bachelor’s degree in Statistics, Computer Science, Data Engineering, Information Systems, or related field
• 5+ years of data engineering development experience.

Preferred:

• Master’s degree in Statistics, Computer Science, Information Systems, Data Engineering, or related field

Skills and Abilities

• Required: Advanced experience with data engineering development languages (ex.: Python, Scala)

• Extensive experience with database platforms (ex.: Snowflake, Oracle, MS SQL Server, etc.)

• Experience with Data Intelligence platform (ex.: Databricks, Snowflake)

• Experience with DevOps and Infrastructure as Code (IaC) tools such as Jenkins, Terraform, CloudFormation

• Knowledge of AWS technologies (ex.: EMR, Step Function, Lambda, EC2, S3, RDS, Dynamo, Bedrock, etc.)

• Basic familiarity with Linux/UNIX command line access.

• Ability to quickly adapt to new methods, work under tight deadlines and stressful conditions

• Ability to work well within a team environment, participate in department/team projects and balance detail with departmental objectives

• Strong oral and written communication skills, demonstrating the ability to convey business terminology that is meaningful and well-received

• Strong ability to handle multiple projects simultaneously

• Ability to resolve conflict and foster teamwork

• Ability to complete requested tasks through independent, self-managed work habits

• Preferred: Ability to liaise with individuals across a wide variety of operational, functional and technical disciplines

• Ability to translate business needs and problems into viable/accepted solutions

• Investigative, analytical and problem-solving skills

• Experience with Java or C#.

• Familiarity with Domino Data Lab and Databricks

• Knowledge of insurance risk analysis.