Welcome to Resideo, where we're on a mission to transform homes into intelligent, efficient, and secure living spaces through the power of IoT-connected devices. As a Lead Data Scientist on our Home Analytics team, you'll play a pivotal role in extracting actionable insights from complex time-series data, making a direct impact on the comfort and safety of homes worldwide. 

As part of this initiative, we are looking for a Lead Data Scientist to help lead our LifeWhere product through the adoption of state-of-the-art ML methods that improve monitoring accuracy while delivering metrics and intelligence for program operation at scale. You will collaborate with a team of experts to develop predictive models and algorithms that drive innovation in connected home IoT devices. Success in this role comes from marrying a strong data science background with product and business acumen to deliver scalable data products to our internal and external customers.

 

JOB DUTIES:

Analyze and interpret complex time-series data from connected HVAC systems to build cutting-edge metrics of HVAC performance, generate insights, and create value for our network of pros and homeowners using our IoT solution Develop methodologies and experiments to continuously improve predictive and machine learning algorithms  Help develop end-to-end process machine learning solutions to support program growth and expansion goals Working with cross-functional teams, including Product Managers and Software Engineers, identify critical business problems and develop solutions to support data-driven business decisions Work to democratize data by building and socializing decision tools (e.g., reports, data products, dashboards)

 

YOU MUST HAVE:

10+ years of related industry experience  Experience using Python, R, etc. working with (preferably) time-series data to support data analysis, visualization, exploratory data analysis, feature generation, and model fitting (in addition to other common analysis activities common to machine learning)  Expert in at least one programming language for data analysis (e.g., Python, R), experience with SQL a plus Strong foundational knowledge in project management with the ability to work in a fast-paced, high-visibility environment Industry experience with developing and applying machine learning and statistical modeling in at least one of the following categories: Anomaly detection, Time-Series Methods, and/or Image processing (e.g. convolutional neural networks, auto-encoders)

 

WE VALUE:

Experience with HVAC systems or related industrial applications Experience with IoT sensor data, preferably in the time-series space, working with edge data processing and connected device ecosystems Experience working with Apache Spark (preferably PySpark) Familiarity with modern ML frameworks and libraries including, deep-learning (e.g., TensorFlow, Keras, or PyTorch), Scikit-learn, Numpy, Pandas, and MLFlow. Knowledge and experience with Databricks, Jupyter notebooks, Git, AWS or Azure cloud environments Detail oriented and willing to learn new skills and tools Experience working with cross-functional teams and an ability to communicate clearly and effectively to technical and non-technical audiences A continuous learning mindset with a willingness to stay updated with the latest trends and technologies in data science and machine learning.

 

WHAT'S IN IT FOR YOU:

Life and health insurance Life assistance program Tuition Reimbursement Retirement plan (Immediate eligibility for 401K) Vacation & holidays (Enjoy work-life balance)

 

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