Note: The job is a remote job and is open to candidates in USA. Motion is seeking its first Senior Data Scientist to build the analytical foundations that transform industrial telemetry into customer-facing insights, alerts, and predictions. The role focuses on time-series modeling, anomaly detection, forecasting, data strategy, and collaboration with engineering, product, and UI teams to deliver actionable industrial intelligence.
Responsibilities
- **Predictive Insights:** Develop models to predict equipment failure, energy spikes, or operational bottlenecks for our industrial clients
- **Signal Extraction:** Apply statistical techniques to filter out sensor noise and identify the true "events" that matter to a facility manager
- **Infrastructure Stakeholder:** Act as the "internal customer" for the Software Engineering team. You will define the schemas, latency requirements, and data "landing zones" you need to perform high-level analysis
- **The Feedback Loop:** Identify "blind spots" in our current telemetry. You will tell the Backend Engineers exactly what data points we are missing to make our AI and BI layers more effective
- **BI & Visualization Logic:** Partner with UI Engineers to ensure dashboards surface meaningful trends and actionable intelligence, rather than just plotting raw telemetry
- **Feature Translation:** Work closely with the Product team to translate complex predictive models (e.g., anomaly scores, failure probabilities) into intuitive, customer-facing features, alerts, and reports
- **Model Refinement:** Incorporate user feedback from the UI directly into your models. Refine model sensitivity and alert thresholds based on customer feedback, investigation outcomes, and observed false-positive/false-negative patterns
Skills
- Proven experience building predictive models and extracting actionable signals from massive, high-velocity datasets
- Deep mathematical understanding of signal processing, anomaly detection, and forecasting
- You must have extensive hands-on experience manipulating and analyzing time-series data (IoT and sensor data experience preferred, but we are open to time-series experts from other high-volume domains)
- Expert-level skills to explore "Big Data" scales. You can navigate partitioned datasets in Snowflake, BigQuery, or Athena to extract features and validate hypotheses
- Expert proficiency in the standard DS stack (Pandas, NumPy, Scikit-learn, SciPy) and visualization libraries
- Experience taking models from a notebook into a production environment, ensuring they are reproducible, testable, and scalable
- Working knowledge of modern cloud data tooling and infrastructure so you can effectively partner with engineers on how analytical data should be stored, transformed, and served
- Ability to design frameworks for validating data accuracy and model performance in real-world industrial settings
- 6-8+ Years of Data Science:
- (IoT and sensor data experience preferred, but we are open to time-series experts from other high-volume domains)
- * **Industrial Domain Knowledge:** Familiarity with how data is generated by LoRaWAN, BACnet, or Modbus devices
- * **Deep Learning:** Experience with neural networks for complex pattern recognition in time-series data
- * **Domain Expertise:** Prior experience in IoT, Green-tech, Prop-tech, or Manufacturing
Benefits
- Training provided for industrial domain knowledge, including familiarity with LoRaWAN, BACnet, or Modbus devices.
- Remote work option (Columbus, OH / Remote)
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