Develop and deploy predictive and generation models to improve the accuracy of our content and contact suggestion engines,
Use NLP, GPT2, GPT3, BERT, T5, and similar techniques to generate relevant and natural email content that can be used in sales outreach,
Develop and deploy various ML techniques to automate and improve current system functionality,
Continuously experiment and improve on feature improvements.
To excel in this role, you should be:
Motivated and eager to work in a fast-paced technology startup
Knowledgeable and passionate about data science's application to targeted and personalized B2B advertising, sales, and marketing
A critical thinker with demonstrated ability to set and attain individual and team goals in complex, resource-strained environments
An excellent analytical and problem-solver who can communicate effectively to bridge the business and technical teams, even those who are remote
Excellent verbal and written communication skills

Чем Вы должны обладать

Обязательно

In-depth understanding of the entire lifecycle of machine learning product development, from inception to production
4+ years of proven experience in building suggestion engines and predictive models for sentiment analysis, content generation, and contact/lead scoring
4+ years of developing and deploying ML models in R&D and production environments using NLP, GPT2, GPT Neo, GPT3, BERT, T5, and similar techniques
6+ years in designing, developing, and implementing big data and/or data science applications
High level of Proficiency with Python, Java, SQL, SAS, Spark, Scala, R, and other programming languages
Solid understanding of CRM solutions (ideally Salesforce)
Ability to translate business challenges to practical and actionable technical solutions.

Желательно

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, sci-kit-learn, H2O, Spark MLlib, etc)
Experience developing, testing, and deploying APIs
Experience building applications based on Microservices Architecture
Experienced with deploying and managing infrastructures based on Docker, Kubernetes, or OpenStack, and Google Cloud Platform