Senior Data Scientist, Privacy Engineering

Senior Data Scientist, Privacy Engineering

Senior Data Scientist, Privacy Engineering Geotab is a global leader in IoT and connected transportation and certified “Great Place to Work.” We are a company of diverse and talented individuals who work together to help businesses grow and succeed, and increase the safety and sustainability of our communities.
Geotab is advancing security, connecting commercial vehicles to the internet and providing web-based analytics to help customers better manage their fleets. Geotab’s open platform and Geotab Marketplace, offering hundreds of third-party solution options, allows both small and large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day,





Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes.
Our team is growing and we’re looking for people who follow their passion, think differently and want to make an impact. Ours is a fast paced, ever changing environment. Geotabbers accept that challenge and are willing to take on new tasks and activities - ones that may not always be described in the initial job description. Join us for a fulfilling career with opportunities to innovate, great benefits, and our fun and inclusive work culture. To see what it’s like to be a Geotabber, check out our blog and follow us @InsideGeotab on Instagram.
Who you are:
We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Senior Data Scientist, Privacy Engineering to work very closely with Geotab’s Data Privacy Advocate,





Data Science team, Data Product teams, and Data Operations team.
What you'll do:
The Senior Data Scientist, Privacy Engineering will be to continually assess and reassess the data from a motivated intruder attack perspective to ensure that aggregated and anonymized data-sets cannot be reidentified and to improve anonymization algorithms. These data layers are used across the Data & Analytics department for internal and external products. Furthermore, they will also be driving research efforts to analyze the safety performance of Geotab’s Generative AI offerings.
How you'll make an impact:
Evaluate and optimize pipelines and architecture to ensure data flows remain privacy compliant.






Stress-test existing privacy controls and filters to demonstrate effectiveness and look for opportunities to modify controls and filters to improve the balance between data protection and data utilization.
Design models and data transformations to develop advanced encryption and anonymization techniques for Geotab’s PII and geo-spatial datasets.
Build and conduct motivated intruder attacks on aggregate datasets and further developing Geotab’s innovative anonymization techniques for geo-spatial data.
Conduct technical investigations in the event of a data incident.
Research and develop methodologies and strategies to encrypt and anonymize data.
Research and keep up to date on data privacy/protection best practices from a technical perspective.






Drive cutting-edge research on generative AI safety, privacy and Responsible AI initiatives, including contributing to red teaming exercises aimed at identifying and mitigating potential risks, biases, and vulnerabilities.
Collaborate to develop innovative solutions that enhance AI safety, fairness, and robustness, while gaining hands-on experience in ethical AI practices.
Engage in the design and implementation of experiments, data analysis, and model development, playing a key role in shaping the future of responsible AI technologies.
What you'll bring to the role:
5-8 years experience as a Data Scientist or a similar role as a privacy or security engineer.
BS degree (MSc or PhD preferred) in computer science, computer engineering, information systems,





privacy engineering or related field of study.
Familiarity with AI/ML frameworks, Responsible AI practices and Generative AI privacy.
Thorough knowledge of programming languages (e.g. Python & SQL) and object-oriented programming.
Thorough knowledge of Big Data tools and Data Mining/Warehousing Programs (e.g. Google BigQuery).
Experience working with geo-spatial datasets.
Experience with machine learning techniques (e.g. Scikit-learn, Tensorflow).
Experience using/building business intelligence tools (e.g. Superset) and data frameworks.
Demonstrated experience driving privacy initiatives end-to-end and designing/implementing technical solutions for complex privacy challenges.






Experience with privacy-preserving techniques like differential privacy, federated learning, or alike.
Knowledge of data anonymization and pseudonymization techniques.
Experience with penetration tests and security audits.
Familiarity with global privacy regulations such as GDPR, CCPA, and HIPAA.
Excellent communication skills (verbal and written), ability to influence without authority.
Entrepreneurial mindset and comfortable in a flat organization.
If you got this far, we hope you're feeling excited about this role! Even if you don't feel you meet every single requirement, we still encourage you to apply.

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