Module Lead - Data Science (Immediate Joiners Preferred)

Company Overview

BOLD is revolutionizing the career landscape by empowering individuals to discover and develop their professional paths. Our recent acquisitions of Monster and CareerBuilder will expand our global reach and impact. With a range of brands like FlexJobs, Zety, and Sonara and more, we provide jobseekers with the tools to create impressive resumes and connect with employers. BOLD fosters adynamic, inclusive culture that prioritizes innovation and growth. So don't wait and join us in shaping the future of work and redefining successful careers

Position Overview

As the newest addition to our existing Data Science team, youll combine your analytical skills andbusiness knowledge to deliver key insights to our Product and Management teams. Youll help driveproduct development using our vast user data sets to enhance our current products and to help us findinferences and relationships in this data to build new products More towards the role required

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 thatleverage 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 changingrequirements.
• 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 leadershipto them.
• Rises above detail to see broader issues and implications for whole product/team

Key Requirements

• Knowledge and experience using statistical and machine learning algorithms includingregression, instance-based learning, decision trees, Bayesian statistics, clustering, neuralnetworks, deep learning, ensemble methods
• Expert knowledge in Python.
• Experience in using large language models.
• Experience infeature selection, building and optimising 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.