- LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide 360-degree view of the digital consumer, fuel machine learning capabilities and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions and turn unstructured data into a valuable business asset.
- We specialize in Predictive Modelling, Marketing Analytics, Big Data Analytics, Advanced Analytics, Web Analytics, Data Science, Data Engineering, Artificial Intelligence and Machine Learning Applications.
- LatentView Analytics is a trusted partner to enterprises worldwide, including more than two dozen Fortune 500 companies in the retail, CPG, financial, technology and healthcare sectors.
● Combine statistics, NLP, and machine learning techniques to create scalable solutions for business problems
● Extensive ML and Deep Learning (NLP focus) experience
● Hands-on experience with text preprocessing, named entity recognition and entity linking, topic modeling, document classification, and summarization
● Experience with sci-kit-learn and pandas; preferably also PySpark, Tensorflow, Pytorch, MLFlow, and NLP packages like spaCy and NLTK
● Focus on scalability, performance, service robustness, and cost trade-offs.
● A continuous drive to explore, improve, enhance, automate, and optimize systems and tools to best meet evolving business and market needs.
● Attention to detail, coupled with the ability to think abstractly.
● Create data tools for analytics and data scientist team members that assist them in building and optimizing our product.
● Keen to learn new technologies and apply the knowledge in production systems.
● Data Engineer Skills: Python, Pandas, PySpark, ML, NLP, PySpark, NLTK.
● Good to have: Experience working with cloud-based stacks (either AWS, Azure, GCP)