FocusKPI is looking for a Machine learning Engineer to work for our client, one of the largest retailers/e-commerce companies in the U.S.A.

Our client is seeking an experienced Machine learning Engineer with hands-on experience designing and developing data platforms. You will own the design, development, and maintenance of the client's client's client's data platform, enabling us to make effective data-informed decisions across various business disciplines. You will be part of cross-functional efforts with the product, backend engineering, and data science to build a next-level data platform that scales and supports all the client's business and data products. In this role, you will have the opportunity to interact with different functional areas within the business and influence decision-making in a fast-growing mobile communications start-up.

In this unique position, individuals will be at the intersection of ML Engineering and Data Science and perform tasks supporting our advanced measurement products. Strong technical skills, combined with knowledge of ML engineering, data science/statistics concepts, and excellent communication/interpersonal skills, are key to success.

Work Location: Remote in the U.S.

Duration: 6 months contract with potential for extension and conversion, depending on budget and performance

Pay range: $50/hr to $65/hr

Responsibilities:

• Own the client'sclient's data warehouse, pipeline, and integration points between various business systems.
• Develop tools to monitor, debug, and analyze data pipelines to ensure data quality and reliability. Troubleshoot data issues and build customized reports to investigate key business questions.
• Explore available technologies and develop solutions to continuously improve our data quality, workflow reliability, and scalability. Perform capacity planning and cost estimates of proposed solutions.
• Design, Develop and support new and existing batch and real-time data pipelines and recommend improvements and modifications.
• Be a champion of the client's data ecosystem by working with engineering and infrastructure to implement data strategy for governance, security, privacy, quality, and retention that will satisfy business policies and requirements.
• Communicate strategies and processes around data modeling and architecture to multi-functional groups and senior-level management. Identify, design, and implement internal process improvements.
• Implement the best practices and standards for data definitions.
• Manage data infrastructure to grow and support the Data Science team in relation to the construction of performant ML-based data products.

Qualifications:

• Bachelor's or Master's degree in engineering, statistics, or related field
• Advanced coding skills utilizing Python and SQL
• Data visualization experience is required
• Must have productionizing experience (building pipelines, deployment, automation, scaling, model drift, saving model artifacts, cloud integration, monitoring, orchestration (airflow), MLOPS practices)
• Understanding of codebase management concepts, code review, Github, and testing
• Good working knowledge of Cloud platforms (GCP preferred) and Airflow D.A.G. development
• Understanding of data science concepts, statistics, and modeling
• Strong communication skills interfacing with internal and external stakeholders
• Proactive, curious team player with project management skills
• Passionate about working in a fast-paced agile environment

 Preferred Qualifications:

• Experience in measurement solutions (marketing mix, multi-touch attribution, campaign lift, etc.)
• Experience with advertising, measurement, and/or digital marketing analytics
• Experience with advertising technology platforms, Ad servers, D.S.P.s, D.M.P.s, etc.
• Experience in front-end languages (HTLM, CSS, JavaScript, etc.) and frameworks

Thank you!

FocusKPI Hiring Team

Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a U.S. company headquartered in Silicon Valley, California with an East Coast office in Boston, Massachusetts.

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