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Lead Data Scientist

1 month, 3 weeks ago
United States
Full-time
Lead
Data Scientist
Data Science and Analytics
AWS Azure BERT CI/CD Deep Learning Docker GCP GPT Helm Hugging Face Keras Kubernetes LLM Machine Learning Microservices NLP NLTK NumPy Pandas PyTorch Scikit-learn spaCy TensorFlow
Apply Now
Smarsh

Smarsh

Smarsh provides cloud-based archiving and compliance solutions that help organizations in regulated and litigious industries manage the risks associated with their electronic communications across more than 80 channels.

IT Services
251-1K
Founded 2001
$44M raised
View All Jobs 21

Description

  • Collect, analyze, and interpret small and large datasets to generate insights for statistical and machine learning methods.
  • Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases.
  • Develop machine learning models and analytics using established workflows while identifying opportunities for optimization and improvement.
  • Perform data annotation, quality review, exploratory data analysis, and model fail-state analysis.
  • Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.
  • Provide guidance to clients and prospects on machine learning model and analytics fine-tuning and development processes.
  • Mentor junior team members on model development and exploratory data analysis.
  • Work with product managers to translate project requirements into technical tasks and team workflows.
  • Collaborate with data scientists, researchers, engineers, and business leaders across end-to-end data science initiatives.
  • Continue self-directed professional development in data science and applied machine learning.

Requirements

  • Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology.
  • Experience with data science and machine/deep learning frameworks and tools such as scikit-learn, H2O, Keras, PyTorch, TensorFlow, pandas, numpy, caret, or tidyverse.
  • Command of data science and statistics principles, including regression, Bayes, time series, clustering, precision/recall, AUROC, and exploratory data analysis.
  • Strong knowledge of programming concepts such as split-apply-combine, data structures, and object-oriented programming.
  • Solid statistics knowledge, including hypothesis testing, ANOVA, and chi-square tests.
  • Knowledge of NLP transfer learning and models such as word embeddings, BERT, SBERT, HuggingFace, and GPT variants.
  • Experience with NLP toolkits such as NLTK, spaCy, or Nvidia NeMo.
  • Knowledge of microservices architecture and continuous delivery concepts in machine learning, including Helm, Docker, and Kubernetes.
  • Familiarity with deep learning techniques for NLP and with LLM tools such as Ollama and LangChain.
  • Excellent verbal and written communication skills.
  • Proven ability to collaborate effectively on cross-functional teams.
  • Master’s or PhD in Computer Science, Applied Math, Statistics, or a scientific field preferred.
  • Familiarity with cloud platforms such as AWS, GCS, or Azure preferred.
  • Experience with automated supervision, surveillance, or compliance tools preferred.

Benefits

  • Base salary range of $166,000 to $214,000 per year.
  • Bonus programs discussed during the recruiting process.
  • Compensation determined by factors including experience, education, location, specialty, training, and internal equity.
  • Remote work option available.
  • Opportunity to work across Atlanta, New York, or remotely in the U.S.

Interested in this position?

Apply directly on the company website

Apply Now

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