Description:

As a Data Scientist at Smarsh, you will analyze a wide range of unstructured communications data to solve customer problems through attentive listening, planning, and innovative thinking.
The role involves collaborating with Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions across various tools and platforms.
You will perform both independent and team-based research, generating insights from large data sets while managing day-to-day data requests and analysis.
The position offers exposure to machine learning and analytics research, allowing you to interface with business leaders, machine learning researchers, data engineers, and other data scientists.
Responsibilities include the development of machine learning models, data annotation, exploratory data analysis, reporting methodology and results, and providing client guidance in model development processes.
Daily tasks will consist of 50% exploratory data analysis and annotation, 20% stakeholder interaction to understand modeling needs, and 30% data science experiments and model building.

Requirements:

A solid knowledge of statistics, including hypothesis testing, ANOVA, and chi-square tests is required.
You must have a command of data science and statistics principles such as regression, Bayes, time series, clustering, and exploratory data analysis.
Understanding and experience with NLP techniques in traditional pipelines and familiarity with deep learning techniques for NLP are essential.
Excellent verbal and written communication skills are necessary.
Proven collaboration skills and the ability to thrive in a team environment are required.
A Bachelor’s degree in Computer Science, Applied Math, Statistics, or a related scientific field is mandatory.
Approximately 2 to 5 years of experience working with data and analytics is required, including experience with Python.
Familiarity with SQL and noSQL databases is necessary, along with knowledge of "Big Data" frameworks like Hadoop, Spark, and Kafka being a plus.
Experience with data science and machine/deep learning frameworks such as scikit-learn, H2O, Keras, PyTorch, TensorFlow, pandas, and NumPy is required.
Experience using Git, Linux/Unix, and IDEs is necessary.

The salary for this position ranges from $120,000 to $130,000 per year, based on various factors including experience, education, and location.
Any applicable bonus programs will be discussed during the recruiting process.
Smarsh promotes a culture of lifelong learning and innovation, valuing collaboration and diversity within the organization.
The company has received awards for being one of the Best Places to Work, highlighting its commitment to developing its people and fostering a positive work environment.