Depending on qualifications, candidates may be hired at different levels. We have multiple positions available. The Senior Data Science Engineer will contribute to our mission through the design, development, implementation, and maintenance of high performance parallel and distributed systems. The position will lead the development of our data processing systems and their interfaces, which support our data science efforts, with a focus on enabling scalable, high performance, distributed computing environments.
The Senior Data Science Engineer is responsible for researching new data processing technologies, building prototypes as needed, and making recommendations to leadership. The position will contribute to the implementation of machine learning and statistical algorithms, including making them more efficient and scalable. As a key member of the Data Science team, this position will work closely with the scientists and will contribute to the modeling and data mining efforts as desired and needed.
Data Science Infrastructure Design, Development, and Operations (50%):
- Lead architectural planning, design, development, deployment, and management of analytical environments capable of ingesting, processing, and analyzing large, diverse data sets containing structured and unstructured elements;
- Determines high level system integrations, primary dependent systems and infrastructure needed to implement the proposed business idea;
- Develops holistic solution architectures ensuring that all architectural aspects of the system including data, application, infrastructure and security are addressed;
- Develop high performance parallel or distributed computing environments, as needed, and including those based on the Apache Stack, in support of key data science capabilities;
- Analyzes architecture portfolios to assess opportunities for improvement and identify changes needed to meet strategic business needs;
- Modify analytical architectures over time as technologies and DSAL needs evolve.
Data Science Research Support (40%):
- Participate in the definition and planning of analytical projects to solve complex business problems as the key technical resource in the areas of data processing and scalable analytical and computational platforms;
- Support quick turnaround for data science projects that provide time sensitive insights by facilitating ingestion, transformation, and processing of data, by developing software or scripting for efficient analytical processing, by rapidly deploying visualization or business intelligence tools and dashboards, or by contributing other technical skills, including software development, as appropriate;
- Maximize the predictability, efficiency, effectiveness, and maintainability of data science-related infrastructure elements with a focus on analytical compute environments;
- Develop means for automating data- and analytics-related systems and processes, as appropriate, to support data science activities.
Technology Strategy (10%):
- Responsible for analyzing business and technology trends related to data architecture, data engineering, data management, and high performance computing to provide expertise to management and resources within DSAL, the Venture Capital group, and other areas of the Business Development division;
- Participates in the development of policies, standards, and guidelines that direct the selection, development, implementation, and use of architecture technologies within the unit;
- Organizes technology strategies into integrated roadmaps to guide initiative planning and scheduling;
- Communicate data and computational methodologies and techniques for other groups within American Family (I/S, SDA, affiliates, etc.), as appropriate;
- Function in a collaborative technical consultancy role to routinely contribute technical expertise in discussions with senior management.
- Demonstrated experience providing customer-driven solutions, support or service;
- Advanced knowledge and experience using a variety of programming languages to implement and operate data science infrastructure assets (e.g., Scala, Python, Java, R, C/C++ );
- Demonstrated entrepreneurial experience working with technology focused startups;
- Demonstrated experience developing and managing complex technical projects involving parallel or distributed computing, including Hadoop, the Apache Stack (Spark, Storm, Kafka, etc.), and related technologies;
- Demonstrated experience working across a broad range of information technology domains, including application, data, infrastructure, and security with specific expertise in design, development, and deployment of data- and analytics-related platforms and tools;
- Demonstrated experience working with or on a Data Science team and familiarity with data mining and machine learning techniques;
- Extensive knowledge and understanding of data management strategies and roadmaps as well as data architectural design models;
- Familiarity with a wide variety of data formats and processing methodologies;
- Familiarity with relational database design and SQL scripting;
- Strong willingness to adapt, pivot, and learn as needed to address emerging opportunities and challenges;
- Willingness to contribute technically in whatever manner is needed to get the job done.