Data Science Engineer - System.AI in Andover

For this U.S. based position, the expected base salary is $160,722.00 – $189,800 per year. Additional short-term incentive compensation is a typical part of our compensation structure and would be in addition to the above-stated range. The compensation range for this full-time position applies to candidates located within the United States. Our salary ranges are determined by reviewing roles of similar responsibility and level. Within the salary range, individual pay is determined by several factors including performance, knowledge, job-related skills, experience, and relevant education or training.

Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits), flexible work arrangements, paid family leaves, 401(k) + match, well-being and recognition programs, 12 holidays per year, 15 days of paid time off per year (pro-rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.

You must submit an online application to be considered for the position. The position will remain posted for approximately 60 days.

Job Description: Contribute to critical data science engineering for System.AI, a Global ETO Service Center of Excellence that delivers true system level predictive outcomes. Develop, adapt, and deploy System.AI/ EcoCare analytics (services for condition-based maintenance). Stack solutions using various platforms to suit specific client requirements. Work with Subject Matter Experts (SMEs) and labelled client data sets to develop insights that drive risk management and insights to support condition-based maintenance. Minimise interventions, optimise interventions, and optimise client SLA's. Liaise with key clients to design and optimise service solutions, to then integrate within existing environments and optimise existing infrastructure. Recommend and deploy enhancements to cloud solutions. Recommend and develop enhancement instrumentation and edge solutions to improve analytic outcomes. Enhance knowledge of existing SE solutions and assist in development of broader SE Edge solutions. Support data engineering, data cleansing, and normalisation for industrial time series, alerts, and alarms. Contribute to analytic development through model definition and development, as well as use of case definition.

Position eligible for remote work up to 3 days/wk.

Requirements: Master’s degree or equivalent in Data Science or related field and 5 years of experience in data engineering within an industrial, machine learning, or Azure environment. Pre-/post- Master’s degree experience is acceptable. Experience must be post-Bachelor’s degree. Academic background, internship, or work experience to include: Programming languages including Python, SQL, or R; Machine learning models to include: Supervised and Unsupervised Learning, Classification Models, Cluster Analysis, Neural Networks, and Fuzzy Logic; Data platforms to include: DataBricks or Snowflake; Performing statistical analysis using TensorFlow, machine learning models, and data mining; Git or Jira; and Industrial Asset model creations and management, along with use of industrial applications and services.

To Apply: Visit and search Req#136957.

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