The Senior Data Scientist will lead Data Science initiatives by developing AI capabilities, breaking down complex problems, and collaborating across teams to produce impactful, production-grade work.
Senior Data Scientist
This role combines strong Data Science expertise with the ability to independently lead impactful, production-grade work in complex environment.
The role focuses on developing AI capabilities on top of complex data in a security product environment. It requires independent thinking, analytical rigor, curiosity, flexibility, and strong technical ability. It also requires leading work end-to-end, breaking down complex problems, conducting structured research, and collaborating effectively across teams.
Key Responsibilities
- Lead Data Science initiatives from problem definition through validation, production deployment, and monitoring
- Develop AI-driven capabilities, including, domain-adapted models, prediction, anomaly detection, classification and AI agents
- Adapt and fine-tune LLM-based solutions
- Break down complex problems into clear components and drive structured research and iterative development
- Choose the right approach for each problem, starting from simple baselines and progressing to more advanced methods when needed
- Design solutions with awareness of production constraints and system limitations
- Help shape solution architecture
- Work closely with product, engineering, and other stakeholders across the company
- Present findings, ideas, and results clearly at different levels, from technical peers to managers
- ·Support team knowledge sharing, brainstorming, and guidance of other team members
- M.Sc. in Data Science, Operation research, Statistics, Mathematics, or a related quantitative field
- At least 5 years of hands-on Data Science experience, delivering end-to-end solutions into production environments
- Strong applied AI experience and deep understanding of model behavior in practice
- Strong Python skills and experience with the modern Data Science ecosystem, including NumPy, Pandas, Scikit-learn, and deep learning frameworks
- Good understanding of LLMs and model adaptation methods
- Experience working with SQL, databases, and data systems
- Strong problem-solving skills, analytical rigor, and ability to work independently
- Excellent communication and teamwork skills
- Curiosity, flexibility, and eagerness to continuously learn new techniques and technical skills
Advantage
- Experience with graph technologies and network-structured data
- Experience designing AI agents or multi-step reasoning systems
- Background in network security, policy management, or compliance-related domains
- Experience with production services, APIs, or integration of Data Science solutions into product environments
- Experience developing solutions for enterprise environments with operational or architectural constraints
Top Skills
Deep Learning Frameworks
Numpy
Pandas
Python
Scikit-Learn
SQL
Similar Jobs at Tufin
Security • Cybersecurity
As an AI Engineer, you will design, build, and deploy AI applications, integrate machine learning models, and ensure reliable system performance.
Top Skills:
DockerGoJavaKubernetesPython
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

