Data Science Intern

Who We Are

DoubleVerify is an Israeli-founded big data analytics company (Stock: NYSE: DV). We track and analyze tens of billions of ads every day for the biggest brands in the world.We operate at a massive scale, handling over 100B events per day and over 1M RPS at peak, we process events in real-time at low latencies (ms) and analyze over 2.5M video years every day. We verify that all ads are fraud free, appear next to appropriate content, appear to people in the right geography and measure the viewability and user’s engagement throughout the ad’s lifecycle.

We are global, with HQ in NYC and R&D centers in Tel Aviv, New York, Finland, Berlin, Belgium and San Diego. We work in a fast-paced environment and have a lot of challenges to solve. If you like to work in a huge scale environment and want to help us build products that have a huge impact on the industry, and the web - then your place is with us.

What You Will Do

As a Data Science Intern on our team (working part-time, 20 hours a week, over the course of a year while you pursue your M.Sc.), you will:

• Own a new research project - You’ll be assigned a specific, cutting-edge project-ranging from agent oriented process automation and improvements to novel data generation approaches-and take it from initial concept to proof of concept.
• Explore advanced AI methods - Dive into areas such as reinforcement learning, LLM-based solutions, automatic prompt refinement and engineering, few shot/zero shot learning. You’ll experiment with the latest techniques, study relevant research, and adapt them to suit our organizational needs.
• Collaborate and learn - Work closely with a dedicated mentor and experienced data scientists. You’ll participate in brainstorming sessions, receive ongoing feedback, and integrate best practices as you refine your ideas.
• Prototype and iterate - Rather than building large-scale production systems, your focus will be on rapid experimentation. Gather insights, refine models or algorithms, and present potential solutions that could shape future products.
• Influence and inspire - Your research findings and innovative ideas can inform the next generation of our platforms and processes-having a real impact on how we tackle data challenges in digital advertising.
  
  

• Education
• Currently enrolled in an M.Sc. (or higher) degree in Computer Science, Engineering, Mathematics, or a closely related field.
• Research mindset
• You’re excited by the latest ML/AI research-whether it’s generative modeling, reinforcement learning, or prompt engineering-and love investigating new techniques to solve complex problems.
• Technical foundations
• Academic or hands-on exposure to ML or data science projects.
• Comfortable coding in Python and SQL.
• Basic understanding of agent based workflows-or willingness to learn. Bonus if you have hands-on experience with AI tools and frameworks such as Cursor, LangChain, LangGraph, Auto-GPT / GPT-Engineer, MCP or similar.
• Strong analytical and problem-solving abilities, with a drive to tackle complex challenges.
• Team and communication
• Collaborative mindset with strong communication skills-comfortable sharing ideas, progress, and roadblocks with peers and mentors.
• Driven by curiosity and a desire to explore uncharted territory in AI.
• Nice to have
• Familiarity with computer vision and NLP.
  

• Research-driven environment: You’ll work at the forefront of AI and ML innovation, exploring cutting-edge topics-like agent-based solutions or few-shot classification-that will become tomorrow’s industry standards.
• Mentorship and growth: Benefit from frequent interactions with subject matter experts, receiving regular guidance to deepen your technical and professional skills.
• Impact: Your contributions will shape cutting-edge classification tools used by top brands worldwide.
• Flexibility: Part-time commitment (20 hours a week) for a full year, balancing your academic research with industry exposure.
• Innovation culture: Be part of a fast-paced, solutions-oriented environment-where new ideas are always encouraged and explored.