Senior Data Science Product Engineer

About the Role

The Senior Data Science Product Engineer plays a key role in the company’s AI strategy. This role offers the opportunity to make a meaningful impact across the whole platform. The Senior Data Science Product Engineer is a hybrid position covering the fronts of technical implementation, technical leadership and product management. This position focuses on envisioning, leading, managing, designing, deploying, and maintaining Data Science and Machine Learning systems, focusing on product roadmap ownership, high-level architecture and practical development, and hands-on implementation.

What You’ll Do

• Technical Leadership: Leading development efforts, mentoring engineers and product managers, and making key architectural decisions that involve Data Science, Machine Learning and AI.
• Cross-functional collaboration: Partner with Sales, Marketing, Customer Support and other departments across the organization for a full end to end ownership from the product and technical perspective as well as internal enablement and customer support.
• Develop greenfield projects and implement proof of concepts, including hands-on coding and connection to the product vision.
• Architect end-to-end Data Science and Machine Learning systems by choosing the best implementation approach out of the holistic AI available tools (Data Science, Statistics, Machine Learning and Generative AI) for the problem to be solved, considering all relevant trade-offs and risks, while maximizing add-on value and minimizing costs, and work hands-on directly in the code with other engineers.
• Manage and lead the UX and UI development for the visualization aspects, Use data-driven solutions to address complex cybersecurity problems.
• Be responsible for the pipeline metrics and work hands-on with MLOps to optimize model and pipeline performance through proper monitoring, data mining, fine-tuning, prompt engineering, and hyperparameter tuning to meet latency and cost requirements.
• Drive technical strategy by evaluating third-party tools versus building in-house solutions to maximize ROI.
• Establish data governance and security standards to ensure the ethical and compliant use of sensitive information within Machine Learning and AI models.
• Be able to create, lead and implement incremental roadmap and engineering development plans based on a product long term vision.

What We’re Looking For

• At least 5 years (or 3 if holding advanced degree) of hands-on experience in product development as an engineer and individual contributor, of which at least 3 years in the area of software, data science or machine learning.
• At least 5 years (or 3 if holding advanced degree) of experience managing, taking to production and giving production support on a combination of several global multi-million dollar products or projects with more than 20 engineers involved and more than 10 other