As a Sr. Data Scientist, you'll analyze unstructured data, develop ML models, guide junior team members, and work with cross-functional teams.
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
What will you bring?
- Bachelor’s degree in Computer Science, Applied Math, Statistics, or a scientific field
- 3-5 years’ experience working with data & analytics
- Experience working with Python, SQL and noSQL databases
- Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse
- Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc…)
- Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)
- Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc…)
- 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
- Knowledge of Agentic Processing
- Familiarity with training and evaluating transformer-based models
- Understanding and Experience of NLP Techniques in traditional pipelines, metrics, process and evaluation for supervised and unsupervised learning.
- Familiarity with Deep Learning techniques for NLP.
- Familiarity with LLMs; using ollama & Langchain
- Excellent verbal and written skills
- Proven collaborator, thriving on teamwork
- Preferred Qualifications
- Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field
- Familiarity with cloud computing platforms (AWS, GCS, Azure)
- Experience with automated supervision/surveillance/compliance tools
About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
Top Skills
AWS
Azure
Carot
Docker
Gcs
H2O
Helm
Keras
Kubernetes
Nltk
NoSQL
Numpy
Pandas
Python
PyTorch
Scikit-Learn
Spacy
SQL
TensorFlow
Tidyverse
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