Bitdefender

Bitdefender is a cybersecurity leader delivering best-in-class threat prevention, detection, and response solutions worldwide. Guardian over millions of consumer, enterprise, and government environments, Bitdefender is one of the industry’s most trusted experts for eliminating threats, protecting privacy, digital identity and data, and enabling cyber resilience. With deep investments in research and development, Bitdefender Labs discovers hundreds of new threats each minute and validates billions of threat queries daily. The company has pioneered breakthrough innovations in antimalware, IoT security, behavioral analytics, and artificial intelligence and its technology is licensed by more than 180 of the world’s most recognized technology brands. Founded in 2001, Bitdefender has customers in 170+ countries with offices around the world. For more information, visit https://www.bitdefender.com

Job Description:

You’ll lead a team to build and deploy analytic solutions that drive Bitdefender’s strategy, working closely with Data Analysis, Data Engineering and Data Warehousing to turn business needs into efficient, robust ML and LLM-powered systems.

Responsibilities:

• Lead the end-to-end Data Science lifecycle: drive data collection, preprocessing, model development, deployment, and ongoing performance monitoring.
• Handle multiple projects independently, ensuring well-documented processes and clear decision records.
• Break down complex challenges into clear, concrete, actionable tasks
• Continuously survey and validate emerging ML and LLM techniques to establish robust standards, select appropriate tools and principles, and codify rigorous best practices across all projects
• Mentor and guide data scientists, offering regular feedback and support to drive their growth.
• Drive the strategic roadmap for the Data Science team, aligning objectives with company-wide KPIs and defining measurable ROI targets.

Requirements:

• 5+ years in applied ML/AI, including at least 1 year hands-on with LLM orchestration frameworks (e.g., Haystack, LangChain, LlamaIndex) and agent-based workflows.
• Proficient Python programming skills with a focus on scalable, maintainable code.
• Proven experience in SQL operations and automating data pipelines using orchestration tools (e.g., Airflow).
• Demonstrated willingness and ability to learn new mathematical and technical methods.
• Great communication skills, capable of translating complex technical concepts into clear, actionable insights.

Nice to Have:

• Master’s degree or PhD in Computer Science, Mathematics, Statistics, Data Science, or a related quantitative field.
• Experience with GCP services and containerization technologies (Docker, Kubernetes).

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