The GARRETT GROUP is seeking an experienced Data Analyst to support advanced analytical, data management, and machine learning initiatives in a dynamic Department of Defense environment.
Responsibilities
Design and manage data collection processes
Analyze large and complex datasets
Develop machine learning models
Create analytical products using Python, R, SQL, and Business Intelligence tools
Support mission decision-making through data visualization and automation
A hands-on data science leadership role focused on developing and deploying machine learning, generative AI, and advanced analytics solutions to address Commercial and Medical business challenges.
Responsibilities
Serve as a hands-on data science practitioner, actively developing models, writing code, conducting exploratory data analysis, engineering features, and supporting deployment of AI/ML solutions.
Develop, validate, and deploy machine learning, generative AI, and advanced analytics solutions to address Commercial and Medical business challenges.
Translate complex business problems into well-defined data science use cases, technical requirements, analytical approaches, and implementation plans.
Build, evaluate, and monitor analytical models and data pipelines, ensuring reproducibility, scalability, explainability, and alignment with CSL data governance standards.
Support the design and implementation of generative AI and LLM-based solutions, including retrieval-augmented generation, knowledge mining, conversational analytics, and agentic workflows.
Requirements
Bachelor’s degree in data science, AI, Computer Science, Statistics, Applied Mathematics, or a related quantitative discipline
Serve as the independent validator of AI Systems, responsible for technical assessment, model risk evaluation, and ongoing monitoring of AI/ML models across The Mutual Group and its member insurance carriers.
Compensation
$100,000 - $135,000 annual base salary depending on experience, qualifications, and geographic location
Responsibilities
Perform independent validation of AI/ML models
Review model design, methodology, and assumptions
Assess training and test data quality
Evaluate performance metrics, thresholds, and benchmarking
Review vendor-provided FactSheets and technical documentation
Requirements
5+ years in data science, model risk management, or AI/ML validation
Global role working with multiple countries across one Therapy Area leading and shaping our Next Best Action (NBA) product capabilities to deliver omnichannel marketing resulting in increased ROI.
Compensation
The salary range for this position is: Bay Area: $226,185 - $292,710. Other US Locations: $205,615 - $266,090.
Responsibilities
Leading and shaping Next Best Action (NBA) product capabilities to deliver omnichannel marketing.
Directly liaise with local brand teams to ensure NBA is well positioned with marketing and operations team in country.
Effective stakeholder management to align NBA enhancements with business priorities.
Working with cross functional teams to co-create and deliver enhancements in a timely manner.
Partner with brand teams to evolve personas, microsegments, recommendation strategies, and customer journeys.
Lead and manage SAP integration, event mesh, and AI core operations across BTP environments, ensuring seamless deployment, monitoring, and troubleshooting of integration flows and event-driven architectures.
Responsibilities
Deploy and configure SAP CPI integration suites
Monitor and troubleshoot integration flows (iFlows) and message processing
Manage security, credentials, and authorization roles
Administer Cloud Connector and hybrid connectivity
Configure and tune NetWeaver Application and OS performance
Support EDPR’s global fleet of generating assets by detecting, reporting, and documenting potential future failures in wind turbines, solar panels, BESS, or other electric systems using condition monitoring and data analytics.
Locations (3)
Houston, Texas, United States
British Columbia, Canada
California, United States
Responsibilities
Detect potential failures using EDPR’s corporate condition monitoring tools to analyze operational data
Communicate clear inspection and repair recommendations to the site managers and technicians
Provide remote support to site personnel to ensure recommendations are addressed correctly
Report the results of the inspection feedback and relay decisions of replacing/repairing the component, material, system, etc.
Assess failure types, remaining useful life, and scope of work required based on inspection pictures
Quantitative Developer - Commodities (Python)
Qube Research & Technologies · Posted Oct 30, 2026
Develop Python applications, quantitative tools and data infrastructure to support trading decisions, research and risk management in the commodities space.
Responsibilities
Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting
Build Python applications and data pipelines to explore, integrate and analyse alternative datasets, including weather and cargo data
Collaborate with Quantitative Researchers and Traders to translate trading ideas and business requirements into production applications and quantitative models
Architect, develop and maintain cloud applications in collaboration with infrastructure engineers, using AWS and related technologies
Develop and apply statistical and machine learning models to support research and trading across Agriculture, Metals and Energy
Requirements
Nice to have: advanced AWS experience
Nice to have: Snowflake experience
Nice to have: parallel or distributed computing
Nice to have: statistical or machine learning models
Nice to have: mentoring junior developers or interns
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