Position Overview
As the newest addition to our existing Data Science team, youll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. Youll 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 productsMore towards the role required
Company Overview
BOLD is an established and fast-growing product company that transforms work lives. Since 2005, weve helped more than 10,000,000 folks from all over America(and beyond!) reach higher and do better. A career at BOLD promises great challenges, opportunities, culture and the environment. With our headquarters in Puerto Rico and offices in San Francisco and India, were a global organization on a path to change the career industry.
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.
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

Keyskills: Natural Language Processing Machine Learning Python Ensemble Regression Neural Networks Deep Learning Random Forest
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