.Are you looking to expand your career into Machine Learning or as a Data Scientist?Are you interested in NLP or data modeling?Are you a talented Python developer based in Mexico and could work full-time within the PST time zone?Join the team remotely for San Francisco-based company from Mexico!!!An exclusive opportunity to work directly with cutting-edge data service technology company, directly with the SourceScrub team.**What is SourceScrub?**SourceScrub is the world's leading data service for firms looking to research, find and connect with privately held companies. Our Private Company Intelligence platform allows deal teams to take a data-driven approach in a traditionally opaque segment of the market. We combine state-of-the-art technology with an unmatched QA process resulting in the freshest and most accurate data set available.SourceScrub provides research and information management systems that incorporate thousands of online sources from trade show exhibitor lists to industry buyers' guides. SourceScrub is working 24/7 to ensure we offer accurate and current data for prospecting investment opportunities. Our sourcing data and prospecting tools promise to save time and increase deal flow.We are seeking a talented Data Scientist or Machine Learning Engineer for a company based in San Francisco. You would be working remotely in the PST time zone with a team creating algorithms and writing functions related to Machine Learning with large data sets.If you have experience with Python and a strong interest in Machine Learning or any experience with platforms related to Machine Learning, we want to talk with you!Very competitive salaries for working remotely in Mexico!- At least 3 years in a professional environment developing Data Science and Machine Learning code - deployed into production. Ability to take ownership and act with some independence - identifying tasks that align with leadership-defined stories and epics.- Experience with python core data science libraries as well as deep learning frameworks - Keras, TensorFlow. Understanding of execution and deployment methods - submitting jobs to clusters, provisioning clusters in cloud-hosted spark environments (Databricks), understanding of the need for GPU processing, and deploying to memory or compute-intensive clusters where appropriate.- Natural Language Processing / Understanding (NLP/NLU) experience. Knowledge of core language processing techniques - n-gram tokenization, document term matrixes, term frequency, stemming, lemmatization, sentiment analysis, and topic modeling. Understanding of language classification and clustering patterns - and ability to implement patterns as deployable code with some independence.- Experience with data prep, tuning, and optimizing NLP models. Knowledge of techniques to mitigate challenges of NLP classification.- Experience with production deployments of models in batch and real-time
