Smarsh is hiring a
Data Scientist

Summary

The job is for a Data Scientist at Smarsh who will analyze unstructured communications data, work with Senior Data Scientists, mentor Associate Data Scientists, and develop machine learning models. The role offers exposure to various problems and solutions associated with taking machine learning and analytics research to production.

Requirements

• Bachelor’s degree in Computer Science, Applied Math, Statistics, or a scientific field
• Approx. 2 to 5 years experience working with data & analytics (including school)
• Experience working with Python
• Familiarity with SQL and noSQL databases
• Knowledge of ‘Big Data’ frameworks like Hadoop, spark and Kafka are a plus
• Familiarity with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse
• Experience using Git, Linux/Unix, an IDEs

Responsibilities

• Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities
• Data annotation and quality review
• Exploratory data analysis and model fail state analysis
• Methodology, results and insights reporting, including model Governance report drafting in collaboration with senior team members
• Client/prospect guidance in machine learning model and analytic fine-tuning/development processes
• 50% exploratory data analysis and annotation
• 20% interaction with stakeholders to understand modeling needs
• 30% data science experiments and model building

Preferred Qualifications

• Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field
• Have 1+ years experience working with NLP, text analytics/classification
• Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)
• Experience with natural language processing toolkits like NLTK, spaCy
• Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes
• Cloud computing (AWS, GCS, Azure)

Benefits

$120,000 - $130,000 a year