Senior Data Scientist at Cambridge Mobile Telematics

Cambridge, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

10 Mar, 26

Salary

184500.0

Posted On

10 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Statistics, Probability, Python, Pandas, NumPy, Scikit-learn, SQL, TensorFlow, Keras, Hadoop, Spark, Data Science, Model Deployment, Data Pre-processing

Industry

Software Development

Description

Cambridge Mobile Telematics (CMT) is the world’s largest telematics service provider. Its mission is to make the world’s roads and drivers safer. The company’s AI-driven platform, DriveWell Fusion®, gathers sensor data from millions of IoT devices — including smartphones, proprietary Tags, connected vehicles, dashcams, and third-party devices — and fuses them with contextual data to create a unified view of vehicle and driver behavior. Auto insurers, automakers, commercial mobility companies, and the public sector use insights from CMT’s platform to power risk assessment, safety, claims, and driver improvement programs. Headquartered in Cambridge, MA, with offices in Budapest, Chennai, Seattle, Tokyo, and Zagreb, CMT measures and protects tens of millions of drivers across the world every day. As a Senior Data Scientist embedded within the Claims Data Science team, you will design, develop, and ship ML/AI systems that support the Crash & Claims product suite. You'll own end-to-end projects that integrate telematics and unstructured data to deliver robust, production-ready models and algorithms that improve and streamline claims processing, triage and overall claims outcomes. This is a hands-on role focused on building reliable, scalable systems, improving model performance and robustness, and productionizing models to meet real-world product needs. CMT is looking for a collaborative, customer-committed, and creative Senior Data Scientist who wants to join us in making roads safer by making drivers better! Responsibilities: Use independent judgment and discretion to develop ML / DL models which pattern driving behaviors and vehicle kinematics in data collected via smartphone sensors Leads projects and solutions through the full development stages, from data pre-processing, modeling, testing, through roll-out with minimum management oversight Write code for debugging complex issues and creating new solutions that will run as part of production systems Support customers’ requests regarding the production ML models and derive deep insights from data Communicate and present the data science work within the data science team as well as to stakeholders across the org and to collaborate across different teams Complete any additional tasks as they arise Qualifications: Bachelor’s degree or equivalent years of experience and/or certification in Data Science, Computer Science, Statistics, Mathematics or Engineering 4+ years of relevant working experience in Data Science Must possess a deep understanding of data science principles, algorithms and practices, such as machine learning, deep learning, statistics and probability Must possess a thorough knowledge of software development process, and proven coding skills using scripting languages e.g. Python, Pandas, NumPy, scikit-learn and SQL Ability to write and navigate code, request data from data sources and code from scratch Experience with deep learning frameworks (TensorFlow, Keras, Torch, Caffe, etc.) and knowledge of Big Data infrastructure (Hadoop, Spark, etc.) will be a plus A great team player and quick learner Nice to Haves: Master’s or PhD preferred Experience working with sensor, telematics or other high-frequency time-series data and the associated data-quality and pipeline challenges Hands-on experience with deploying and monitoring models in production (MLOps best practices, model versioning, CI/CD for ML) Familiarity with modern vision model approaches and practical experience applying them to image and video problems (model selection, evaluation, and deployment) Practical experience with large language models and LLM inference approaches — able to evaluate model tradeoffs and select appropriate models and AI tools for a given task Compensation and Benefits: Fair and competitive salary based on skills and experience, and annual performance bonus Equity may be awarded in the form of Restricted Stock Units (RSUs) Medical, Dental, Vision and Life Insurance, matching 401k, short-term & long-term disability and parental leave Unlimited Paid Time Off including vacation, sick days & public holidays Flexible scheduling and work from home policy depending on role and responsibilities Base Salary Range The base salary range for this position is: $147,600 to $184,500. This range is specifically for Cambridge, MA Additional Perks: Feel great working to improve road safety around the world! Join one of our many employee resource groups including Black, AAPI, LGBTQIA+, Women, Book Club and Health & Wellness Extensive wellness, education and employee assistance programs CMT will do all that is possible to support our employees and create a positive and inclusive work environment for all! Commitment to Diversity and Inclusion: At CMT, we believe the best ideas come from a mix of backgrounds and perspectives. We are an equal-opportunity employer committed to creating a workplace and culture where everyone feels valued, respected, and empowered to bring their unique talents and perspectives. Diversity is essential to our success, and we actively seek candidates from all backgrounds to join our growing team. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability state. CMT is headquartered in Cambridge, MA. To learn more, visit www.cmtelematics.com and follow us on X @cmtelematics.

Responsibilities

Design, develop, and ship ML/AI systems that support the Crash & Claims product suite. Own end-to-end projects that integrate telematics and unstructured data to deliver robust, production-ready models and algorithms.