About JWP Connatix

JWP Connatix is the most comprehensive independent video technology and monetization platform, helping broadcasters, publishers, and advertisers deliver premium streaming and online video experiences while maximizing video revenue across all screens. Our platform powers streaming for over 2,000 media companies, including 80% of the top 25 Comscore US publishers, reaching more than 1B unique users and delivering 30B+ video plays and ad impressions every month.

The Opportunity

We are seeking a Staff Data Scientist with deep programmatic media expertise to architect and drive the next generation of supply-side optimization systems. This is a hands-on role with experience working with product, engineering, and operations. You will help define and execute the the roadmap for supply optimization, lead the design of models and algorithms that maximize publisher yield (margin optimization, price floor prediction), and ensure our systems operate at internet scale with real business impact. You will be part of a small team of data scientists based in the US and Romania, in the AI & Data Science group.

This role is ideal for someone who has built and shipped optimization systems at an SSP or publisher and can blend machine learning, operations research, and practical engineering to solve hard marketplace problems.

What You’ll Do

• Help Lead the Supply Optimization Domain: Set the technical vision and roadmap for optimization across pricing, auction dynamics, demand pathing, and inventory allocation. Play an active role in helping the Chief AI Officer, the Director of Data Science, and the team define the road map
  
  
• Be the data expert: Bring technical fluency and critical curiosity to how data is defined and used. Validate data models, surface inconsistencies, and actively advocate for capturing the data the team truly needs - rather than just using what’s available.
  
  
• Leverage Operations Research: Apply linear/integer programming, stochastic optimization, and queuing theory to tackle, in real time, pacing, routing, margin optimization, and floor price optimization.
  
  
• Scale Real-Time Decisioning: Partner with engineering to build low-latency inference systems that operate across billions of programmatic auctions per day.
  
  
• Experimentation Leadership: Define and oversee simulation frameworks, offline tests, and A/B experiments to validate model performance and business impact.Apply causal inference to measure impact and model performance in environments with shifting traffic patterns (e.g., seasonal changes or publisher inventory fluctuations).
  
  
• Mentor & Guide: Provide technical leadership and mentorship to other data scientists and engineers, raising the bar on modeling, experimentation, and production practices.
  
  
• Cross-Functional Influence: Act as the subject matter expert for supply optimization, collaborating with product, yield ops, and exec stakeholders to align strategy and execution.
  
  
• Innovate for the Future: Stay ahead of industry trends in programmatic supply, SPO, and auction theory; champion new methods (reinforcement learning, causal inference, agent-based optimization).
  
  

What We’re Looking For

• Master’s or PhD in a quantitative field or quantitative social sciences (Computer Science, Statistics, Operations Research, Economics, Applied Math, Political Science, Psychology, Sociology, etc.).
  
  
• 8+ years of experience in data science/engineering, with at least 4 years in programmatic media, ideally at an SSP, exchange, or publisher.
  
  
• Proven track record designing and deploying supply optimization or yield management systems in production.
  
  
• Deep technical expertise in optimization and ML: ML frameworks (XGBoost, CatBoost, PyTorch, TensorFlow, Quantile Regression, Multi-Armed Bandits, Gradient Descent) and OR tools (Gurobi, OR-Tools, CPLEX).
  
  
• Strong programming ability in Python and SQL, bonus points for C#.
  
  
• Domain expertise in online advertising: OpenRTB, header bidding, SPO, auction design, Bid Landscape Modeling, and Floor Price Elasticity estimation..
  
  
• Experience with experimentation platforms, statistical inference, and causal methods.
  
  
• Demonstrated ability to lead technical initiatives, influence cross-functional stakeholders, and deliver business outcomes.
  
  
• Comfortable with making use of AI to speed up development and research cycles.
  
  
• Excellent communication skills: able to explain trade-offs, optimizations, and modeling decisions to execs and engineers alike.
• Must have a valid passport. We are a global company.

Nice to Have

• Hands-on experience building high-throughput, low-latency systems for programmatic decisioning.
  
  
• Experience with reinforcement learning or multi-armed bandits in live marketplaces.
  
  
• Familiarity with modern data and ML infrastructure: MLFlow, Airflow, Docker, K8s, Terraform, AWS.
  
  
• Industry thought leadership: publications, patents, or conference talks on ad tech, optimization, or large-scale ML.