Lead Data Scientist

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🗽 New York – Remote

🗽 New York – Remote

💵 $166k - $214k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Smarsh

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2001

💸 Finance

🏢 Enterprise

☁️ SaaS

💰 Private Equity Round on 2016-01

Finance • Enterprise • SaaS

Smarsh is the global leader in communications data and intelligence, focusing on digital communications compliance and risk management in regulated industries. With over two decades of experience, Smarsh delivers AI-enabled solutions to unlock business insights from communications data at scale. Trusted by 95% of top financial firms and managing billions of messages monthly, Smarsh offers services like chat capture, email archiving, and digital risk surveillance. Their platforms are designed to meet the diverse and evolving needs of financial services, government, healthcare, and other industries, enhancing productivity and ensuring compliance with digital communication governance challenges.

📋 Description

• Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms. • Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication). • 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 • Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards. • Client/prospect guidance in machine learning model and analytic fine-tuning/development processes • Provide guidance to junior team members on model development and EDA • Work 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

🎯 Requirements

• Strong understanding of **financial markets, compliance, surveillance, supervision, or regulatory technology** • 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, Nvidia NeMo • Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes • 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