Job Description

STANLEY Security is a trusted partner for security around the globe protecting over 700,000 buildings in 27 countries on 6 continents. STANLEY Security has solutions to protect people, safeguard assets, secure networks and manage operations. With over 9000 employees, 3500 technicians and 18 monitoring centers, STANLEY Security is a best-in-class provider of frictionless and intuitive health and safety systems for our customers.

This role, reporting to the Director of Product Management for Data Strategy, will lead the process of organizing and leveraging our device generated data.  It will include working with Data Engineering, Data Architects and Data Scientists to enable creation of new products and insights for all of our markets.
Responsibilities

• Work with Product and Organizational leadership to define a vision that will deliver high value to our customers while helping to achieve the financial goals of STANLEY Security.
• Create and execute on roadmap for Data Engineering, to move data from customer facilities to STANLEY Security’s data lake and data warehouse.
• Create and execute on roadmap for data architecture, resulting in clean, consistent and complete data, enabling data science.
• Create and execute on the data science roadmap, resulting in internal and external products.
• Build a prediction service infrastructure, which will allow predictions from models to be delivered in production environments in a highly performant manner.
• Develop and execute an onboarding process to kickoff new data projects rapidly with repeatable and predictable outcomes.
• Bring internal and external solutions to market, working with the solutions teams to achieve market success.
• Exceed revenue and margin targets for the organization.

Required Qualifications

• Bachelor’s degree in a technical discipline
• 2+ years of experience in a Product Owner/Product Manager role

Preferred Qualifications

• Advanced degree preferred (Computer Science, helpful)
• Experience with data ingestion, mining, wrangling, and cleansing (e.g., R, SAS, SPSS, Stata, MATLAB, Minitab, etc.)
• Strong knowledge of analysis tools such as Python, Shell scripting, Tableau, Google Data Studio, Periscope, Metabase, Jupyter, Oracle Analytics, R, Etc
• Experience with AWS Cloud based solutions is a plus.  Other cloud computing systems also acceptable, Azure, Google Cloud, etc.
• Experience working with Engineering teams to overdeliver, on schedule, with high quality
• Experience in Azure DevOps or a CI/CD environment
• Experience with Kinesis, Confluent, Kafka, HubSpot, etc, to develop low latency pipelines
• On-Prem to Cloud Migration
• Experience working with market facing and sales teams
• Familiarity with Security and monitoring ecosystems

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