Senior Data Scientist

Senior Data Scientist

We develop connected safety technology that helps homeowners and organizations identify electrical risks before they become emergencies. Our solutions combine intelligent monitoring, timely alerts, and access to experienced support, with a strong record of protecting homes and communities. The work brings together advanced engineering and a practical commitment to helping people feel safer in their everyday lives. Joining our team means applying your skills to meaningful challenges while collaborating with colleagues who care about innovation, reliability, and measurable impact.

Position Overview

We are seeking a Data Scientist specializing in computer vision and machine learning to design, build, and productionize scalable visual intelligence solutions. You will lead model development and evaluation, implement robust data pipelines and inference services in Python on Linux, and deploy/operate models on AWS. The role balances research-driven experimentation with pragmatic engineering to deliver measurable product improvements and support cross-functional teams.

Key Responsibilities

• Design, develop, and iterate state-of-the-art computer vision and machine learning models to solve image and video analysis problems.
• Implement end-to-end ML pipelines in Python on Linux: data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Preprocess and label large-scale visual datasets; develop data augmentation and image-processing routines to improve model robustness.
• Leverage AWS services (e.g., S3, EC2, SageMaker, Lambda) to train, tune, and deploy models and manage model artifacts and data storage.
• Optimize models for performance, latency and cost; implement techniques for model compression, quantization, and efficient inference where required.
• Build reproducible experiments, maintain training logs, track metrics, and run A/B tests to evaluate model impact in production.
• Collaborate closely with product managers, software engineers, and QA to integrate models into applications and APIs and to translate product needs into technical specifications.
• Write clean, well-documented, and testable Python code; use version control and follow CI/CD best practices for ML delivery.
• Monitor model performance and data drift post-deployment; implement alerting and retraining strategies.
• Communicate results, trade-offs, and technical rationale clearly to both technical and non-technical stakeholders.

Qualifications

• Bachelors or Masters degree in Computer Science, Electrical Engineering, Statistics, Applied Math, or a related field (PhD a plus).
• 10+ years of professional experience as a Data Scientist, ML Engineer, or similar role with demonstrable work in computer vision and machine learning.
• Strong programming skills in Python and experience working in Linux environments.
• Proven experience building and deploying ML models on AWS (S3, EC2, SageMaker or equivalent).
• Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow for image-based tasks.
• Solid understanding of machine learning fundamentals: supervised/unsupervised learning, model evaluation, cross-validation, and hyperparameter tuning.
• Experience with data processing and analysis libraries and tools (NumPy, pandas) and familiarity with distributed processing frameworks (Spark) is highly desirable.
• Experience with gradient boosting libraries (xgboost/LightGBM) and traditional ML algorithms for tabular data is a plus.
• Strong grounding in image processing techniques and computer vision concepts (CNNs, object detection, segmentation, keypoint estimation) is preferred.
• Familiarity with containerization and deployment tooling (Docker, Kubernetes) and CI/CD practices for ML workflows.
• Excellent problem-solving skills, attention to detail, and strong written and verbal communication skills.

For this position you must be currently authorized to work in the United States. We do not sponsor for this position.