Senior Machine Learning Engineer
Company
League Legacy
Location
Chicago, IL
Type
Full Time
Job Description
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud-native and big data principles.
- Build the framework to enable analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Product, Data and Marketing teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and regions.
- Create data processes and tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Advanced working knowledge and experience working with relational databases, query authoring as well as working familiarity with a variety of databases.
- Experience building and optimizing big data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Experience with message queuing, stream processing, and highly scalable big data stores.
- Experience with end-to-end API design, implementation and sustainment.
- Strong analytic skills related to working with unstructured and structured datasets.
- Project management and organizational skills to self-scope and direct on a day-to-day basis.
- Experience supporting and working with cross-product/feature teams in a dynamic environment.
- The ideal candidate should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, Beam, etc.
- Experience with both relational SQL and NoSQL databases, including Postgres, MongoDB, etc.
- Experience with data pipeline and workflow management tools such as Apache Airflow, etc.
- Strong Experience with Code Management + DevOps: Github, Github Actions, Concourse CI, Terraform, Atlantis, etc.
- Experience with Google Cloud Platform (GCP) cloud services: BigQuery, DataFlow, PubSub, CloudSQL, Cloud Storage, Cloud Composer, VertexAI
- Knowledge of the FHIR standard and/or healthcare data
- Experience with object-oriented/object function scripting languages: Python, Go, Scala, Java, C++, etc.
- You should receive a confirmation email after submitting your application.
- A recruiter (not a computer) reviews all applications at League.
- If we see alignment with League's needs, a recruiter will reach out to learn more about your goals. The recruiter will also share the team-specific interview process depending on the roles you are exploring.
- The final step is an offer, which we hope you will accept!
- Prior to joining us, we conduct reference and background checks. Additional checks could be required for US Candidates, depending on the role you are exploring.
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01/28/2023
Views
5
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