Data Scientist will work closely with the Product team and will be responsible for creating predictive models and algorithms. The candidate will focus on developing new tools and methods to improve the performance of the platform and the accuracy of its suggestions. The candidate will possess business intuition and critical thinking to approach problems in innovative ways. He/she/they will have excellent communication skills and will be able to convey complex technical information in plain business terms to company executives and advisors.
– In-depth understanding of the entire lifecycle of machine learning product development, from inception to production
– 3+ proven experience in building suggestion engines and predictive models for sentiment analysis, content generation and contact/lead scoring
– Experience in developing and deploying ML models in R&D and production environments using NLP, GPT2, GPT Neo, GPT3, BERT, T5 and similar techniques
– Experience in designing, developing and implementing big data and/or data science applications
– High level of Proficiency with Python, SQL, Spark, Scala, R
– Solid understanding of Salesforce CRM solutions
– Ability to translate business challenges to practical and actionable technical solutions.
– English level - fluent
– Master’s Degree or higher in Computer Science or a related field
– Proficiency with scalable data extraction tools
– Implementation and operational knowledge Data and Business Intelligence Analytics tools like Tableau, Looker, Thoughtspot, etc.
– Experienced in using AI/ML platforms, technologies, techniques (e.g. TensorFlow, Apache MXnet, Theano, Keras, CNTK, scikit-learn, H2O, Spark MLlib, etc)
– Experience in developing, testing and deploying APIs
– Experience in building applications based on Microservices Architecture
– Experienced with deploying and managing infrastructures based on Docker, Kubernetes, or OpenStack, and Google Cloud Platform
– Professional and personal development
– Comfortable working environment
– 18+ working days paid vacation
– Paid sick leaves
– Medical insurance for employees, for children of employees
– Language classes
– Subscription for pool and gym
– Compensation of visiting professional conferences