Data Science Manager

Optimove is a global marketing tech company, recognized as a Leader by Forrester and a Challenger by Gartner. We work with some of the world's most exciting brands, such as Sephora, Staples, and Entain, who love our thought-provoking combination of art and science. With a strong product, a proven business, and the DNA of a vibrant, fast-growing startup, we're on the cusp of our next growth spurt. It's the perfect time to join our team of ~500 thinkers and doers across NYC, LDN, TLV, and other locations, where 2 of every 3 managers were promoted from within. Growing your career with Optimove is basically guaranteed. 

• Lead, mentor, motivate and inspire a small team of Machine Learning Engineers & Data Scientists.
• Own the model development and release process across all products and internal platforms, including both OptiX and Optimove. 
• Manage the cloud-hosted modelling environment. 
• Operationalize models as APIs working in real-time and batch environments. 
• Monitor production models, ensuring data quality and model performance.
• Develop predictive machine learning models for classification, ranking, and personalization purposes, utilizing multi-modal data including images and text. 
• Leverage LLMs and other cutting-edge technologies to enhance product capabilities. 
• Collaborate closely with product and development teams to define and prepare new ML applications. 
• Analyse performance and continuously improve scoring processes for hosted models. 

• Exposure to a phenomenal array of machine learning domains, including massive-scale search, ranking, NLP, hybridization, classification, multi-modal data processing (images, text, etc.), and far beyond. 
• Leveraging state-of-the-art technologies, including Large Language Models (LLMs), to enhance our products and services.
• Fully real-time architecture for data processing, model development, and deployment. 
• Deploying and enhancing ML frameworks, optimizing for inference, and training/retraining cycles.
• Online testing for models with live data using proprietary A/B/N testing technology to rapidly determine what works (and what doesn't). 
• A super-bright, supportive, and friendly machine learning team to work with in an environment where rapid experimentation is the norm. 
• Regular time allocated to research new methods, build and test proofs-of-concept, and deploy to production instantly if effective. 
• GPU support to efficiently train deep learning models. 

• Minimum 3 years of managing or leading ML or Data Science teams
• Strong programming skills and a good understanding of software engineering principles and clean code practices. 
• Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). 
• Advanced experience with SQL for data querying and manipulation. 
• Experience with Git, Bash, Docker, and machine learning pipelines. 
• Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. 
• Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. 
• Experience with cloud technologies and data storage solutions, including Snowflake.

• Understanding of personalization for various domains, including sports betting and gaming, where it might add value and what best practices look like. 
• Full understanding of recommendation algorithms and their applications. 
• Professional experience in personalization and/or predictive CRM, and micro-segmentation. 
• Experience with CI/CD pipelines and Infrastructure as Code (IaC) tools (Terraform, Bicep, etc.).