WHO ARE WE?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

SUMMARY

As a Sr. Data Scientist at Smarsh, you will be analyzing a wide range of unstructured communications data to address problems for our customers through attentive listening, astute planning, and out of the box thinking to develop solutions and reporting results in an engaging manner.
The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.
This role offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.

HOW WILL YOU CONTRIBUTE?

• Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.
• 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
• Providing guidance to junior team members on model development and EDA
• Working with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team’s tooling, technique and procedures
• Continued self-led personal development

Please refer the Job description for details