Software Engineer- DataScience (Fine Tuning)

Role Overview: You will be joining the Data Science team at BOLD where you will utilize your analytical skills and business knowledge to provide valuable insights to the Product and Management teams. Your main responsibilities will include driving product development by leveraging user data sets, discovering patterns in data, and developing predictive algorithms and models. Key Responsibilities: - Demonstrate ability to work on data science projects involving predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc. - Leverage rich data sets of user data to perform research, develop models, and create data products with Development & Product teams. - Develop novel and scalable data systems in cooperation with system architects using machine learning techniques to enhance user experience. - Knowledge and experience using statistical and machine learning algorithms such as regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods. - Expert knowledge in Python. - Experience working with backend technologies such as Flask/Gunicorn. - Experience on working with open-source libraries such as Spacy, NLTK, Gensim, etc. - Experience on working with deep-learning libraries such as Tensorflow, 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. Qualifications Required: - Experience in feature selection, building and optimizing classifiers. - Should have done one or more projects involving fine-tuning with LLMs. - Experience with Cloud infrastructure and platforms (Azure, AWS). - Experience using tools to deploy models into the production environment such as Jenkins. - Experience with the ontology/taxonomies of the career/recruiting domain e.g. O*Net NR.,