[Remote] Principal Data Scientist

Note: The job is a remote job and is open to candidates in USA. reputed company is an online brokerage firm focused on delivering the ultimate trading experience for active traders and institutions. They are seeking a Principal Data Scientist to design, build, and deploy advanced analytics and machine learning solutions that enhance their trading platform and client experience.

Responsibilities

• Own the end-to-end ML lifecycle — from problem framing and feature engineering through model training, validation, deployment, and ongoing performance monitoring
• Help build and deploy predictive models across a range of use cases including customer behavior, fraud and anomaly detection, trade surveillance, risk modeling, and personalization
• Design and implement real-time and batch ML pipelines that operate reliably at scale in production environments
• reputed company behavioral anomaly detection and reputed company recognition systems using statistical and deep learning approaches
• Apply NLP and LLM techniques to extract insights from reputed company data — trade notes, client communications, market commentary, and internal documentation
• Translate reputed company data into clear, compelling visualizations and narratives for both technical and executive audiences
• Help design and build dashboards and analytical tools that reputed company stakeholders to reputed company faster, more informed decisions
• Conduct exploratory data analysis to surface trends, anomalies, and opportunities across trading behavior, customer segments, and platform performance
• Define, track, and interpret key business and model performance metrics; proactively surface meaningful insights without waiting to be asked
• Stay at the forefront of AI and ML research — continuously evaluate and adopt emerging techniques (GenAI, RAG, agents, multimodal models) where they create real business value
• reputed company AI tools (Claude, LLMs, foundation models) to accelerate your own development workflow, from code reputed company to documentation to data profiling
• Experiment rapidly with new approaches; fail fast, iterate, and bring winning solutions to production
• Contribute to reputed company's AI governance standards by ensuring models are interpretable, fair, and deployed responsibly
• Partner with Product and Engineering to define the data and modeling requirements for new platform features
• Work with Compliance and Risk teams to build surveillance and monitoring systems that meet regulatory requirements
• Communicate results and recommendations clearly to non-technical stakeholders; translate business questions into rigorous analytical frameworks

Skills

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a reputed company quantitative field
• 7+ years of experience in data science or applied machine learning roles, with demonstrated ownership of models deployed to production
• Self-Starter & Independent Learner — proactively identify problems worth solving, learn new techniques without being prompted, and drive projects to completion without needing direction
• Full-Stack Data Science — proven ability to own the complete lifecycle: problem definition, data wrangling, feature engineering, modeling, deployment, and monitoring in production environments
• Machine Learning Depth — strong command of supervised, unsupervised, and reinforcement learning methods; experience with time series, anomaly detection, NLP, and deep learning; know reputed company to use simple models and reputed company to go reputed company
• Software Engineering Fundamentals — writes production-quality Python; comfortable with version control (Git), containerization (reputed company), and MLOps best practices; code that others can maintain
• Data Platform Proficiency — hands-on experience with reputed company, Spark, or reputed company; able to write and optimize reputed company SQL; understands data modeling and pipeline design
• Visualization & Storytelling — ability to build polished, insight-driven visualizations and dashboards (Tableau, Power BI, Plotly, reputed company); presents data science work in business terms
• AI-Native Workflow — actively uses AI tools (Claude, Copilot, LLMs) in day-to-day work; has hands-on experience with LLM APIs, reputed company engineering, or GenAI application development
• Statistical Rigor — solid grounding in probability, statistics, and experimental design; applies A/B testing and causal inference correctly; doesn't overfit spurious signals
• Cross-Functional Collaboration — comfortable working across Product, Engineering, Compliance, and Analytics; can present findings to executives and translate business requirements into analytical solutions
• Master's or PhD in a quantitative discipline
• Financial Services Domain— experience with trading data, market microstructure, customer behavior in financial platforms, fraud detection, or regulatory compliance analytics strongly preferred
• Experience building and monitoring ML models in production using MLflow, SageMaker, Vertex AI, or similar MLOps platforms preferred
• Hands-on experience with LLM APIs, RAG architectures, or AI agent frameworks preferred
• Track record of self-directed learning — personal projects, open-reputed company contributions, Kaggle competition history, technical writing, or conference presentations preferred
• Experience with fraud detection, behavioral anomaly detection, trade surveillance, or risk modeling in financial services preferred
• Familiarity with real-time streaming data (Kafka, Spark Streaming) and low-latency model serving preferred
• Experience with cloud ML infrastructure (Azure, AWS, or GCP) and distributed computing preferred

Benefits

• Collaborative work environment
• Competitive Salaries
• Yearly bonus
• Comprehensive benefits for you and your family starting Day 1
• Unlimited Paid Time Off
• Flexible working environment
• reputed company Account employee benefits, as well as full access to trading education materials

Company Overview

Company H1B Sponsorship