SE/SSE- Data Science (AI/LLM)

Company Overview

Monster and CareerBuilder

Position Overview

As the newest addition to our existing Data Science team, you'll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You'll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products

Required Skills

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods
• Expert knowledge in Python.
• Experience in using large language models.
• Experience in feature selection, building and optimizing classifiers.
• Experience working with backend technologies such asFlask/Gunicorn etc.
• Experience on working with open source library such Spacy, NLTK, Gensim etc
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc.
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc.
• Be a keen learner and enthusiastic about developing software.

Key Responsibilities

• Demonstrate ability to work on data science projects involving NLP, large language models, predictive modelling, statistical analysis, vector space modelling, machine learning etc.
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience
• Collaborates effectively with cross functional teams to deliver end-to-end products & features.
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements.
• Estimates efforts, identify risks, devises and meets project schedules.
• Runs review meetings effectively and drive the closure of all open issues on time
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them.
• Rises above detail to see broader issues and implications for whole product/team.