we are looking for a Data Scientist to join our R&D team. To become part of our journey in helping digital publishers and businesses improve their business growth, empowering meaningful interactions across their digital assets, generating an undeniable increase in revenue, user engagement, conversions, and overall performance.
Long story short, you will:
Design, build, automate, deploy and maintain machine learning production pipelines, utilizing cloud technologies such as cloud AI / Sagemaker.
Building RAG processes and utilizing LLMs for verius needs.
Deploy and monitor models in production (e.g. building artifacts, measuring model drift, etc.).
Implement and evaluate recommender engines and deep-learning techniques, to work in a production environment and run at massive scale.
Apply complex analytical techniques to derive actionable insights with very good communication skills to write and publish internal documentation to be used by technical and business teams.
Design and execute technical processes needed for experimentation to support an array of business problems, including experiment ideation, experimental design, monitoring, data analysis, code review and communication of results.
Keep up with machine learning research and commercial product offerings across a wide variety of machine learning fields
Role Key Deliverables: Own current recommendation engine modeling stack and its development processes (creation/specification of tasks, daily updates and commitment to deliverables), research and deploy incremental improvements.
Requirements: Masters in Computer Science/Statistics/Economics/Engineering or related field with a focus on applied statistics, AI, machine learning, or related fields
5+ years applying machine learning to real-world problems in an industrial setting.
Strong engineering and coding skills, with ability to write high performance production code. Ability to lead, envision and implement improvements of our ML solution and pipelines
Proficiency in Python, SQL, Spark.
Hands-on experience in Machine learning frameworks such as Scikit-learn, TensorFlow, Pandas, Numpy etc.
Strong understanding of evaluation methods for recommender systems and ability to run offline and online using experimental design
Preferred proficiency with data pipelines in Hadoop/Spark in a cloud environment
Ability to write and execute complex queries in SQL against different database architectures
Working knowledge of agile development processes and methodologies
Strong analytical & problem-solving skills, and excellent communication skills
This position is open to all candidates.