דרושים » תוכנה » Applied data Scientist

Required Senior Data Scientist
Realize your potential by joining the leading performance-driven advertising company!
As a Senior Data Scientist on the Algorithms team in our Tel Aviv office, youll play a vital role in designing and deploying machine learning models that power real-time bidding and optimize billions of daily auctions. Youll develop advanced modeling solutions that drive bid optimization, price prediction, and auction strategy while partnering closely with Engineering, Product, and Business teams to bring research into production. Your work will directly improve advertiser performance, publisher revenue, and marketplace efficiency at massive scale.
How youll make an impact:
Design, train, and deploy machine learning models for bid optimization, price prediction, win-rate prediction, CTR/CVR estimation, calibration, and auction optimization.
Own the full machine learning lifecycle, from research and experimentation through production deployment, A/B testing, monitoring, and continuous optimization.
Analyze large-scale marketplace data to identify modeling opportunities and translate insights into measurable business impact.
Partner closely with Product, Engineering, and Business teams to define and deliver scalable machine learning solutions.
Improve the performance, scalability, and reliability of production models serving low-latency, high-throughput traffic.
Mentor junior data scientists and contribute to technical reviews, experimentation best practices, and knowledge sharing across the team.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards

Required Customer-Facing Data Scientist - Demand Forecasting
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.