Principal Data Scientist

Key Skills

Algorithms, Data science techniques, Effective communication skills, Machine learning techniques, MLOps tools, Python Programming, SPARK Programming

Job Description

What You Will Do

• Independently conduct statistical analysis, NLP, and integration of massive datasets from multiple sources, including exploratory analysis, correcting for bias, and validation
• Recommend and implement cutting-edge AI models, including building and tuning LLMs and LLM-powered agents, in a manner that provides reliable solutions for our clients
• Conduct proof-of-concept studies to evaluate multiple competing simulations, models, or forecasts to empirically justify your recommendations for action
• Create deployable data science solutions that implement research findings using MLOps best practices
• Define, plan, and execute agile data science R&D, prioritizing iterative development and collaboration with stakeholders
• Use your curiosity and passion for data to answer complex questions over real-world datasets comprised of billions of rows
• Communicate plans, results, models, and insights to stakeholders, clients, and non-technical audiences

What You Will Bring to SymphonyAI

• Master's or Bachelor's degree in a quantitative or technical field such as Computer Science, Physics, Mathematics, Econometrics, or Engineering
• 5+ years of professional experience deploying production data science models that created insights from data at large scale
• 2+ years of leading large, impactful R&D projects
• Deep understanding and ability to communicate machine learning methods, their strengths, and their limitations
• Familiarity with MLOps principles of model registries, feature stores, retraining strategies, and experiment tracking
• Curiosity, clarifying questions, a passion for learning new things, and perseverance in the face of uncertainty
• Ability to communicate clearly in meetings and written documents, consider options presented by others, and reach a balanced technical opinion
• Strong business acumen to relate the needs of the customer to the data science solutions we can build with our products

Key technical proficiencies:

• Natural language implementations including TFIDF, LSTMs, embeddings, attention, transformers, and LLMs
• Designing and writing scalable production software including Python and Spark
• Data science algorithms, data quality checks, cross-validation, and parameter tuning methodologies
• Software engineering best practices such as version control and ML deployment methods

 Preferred skills and experiences:

• PhD in a quantitative or technical field such as Computer Science, Physics, Mathematics, Econometrics, or Engineering
• Building and deploying to orchestration frameworks such as Airflow
• Familiarity with financial markets and fixed-income securities
• Experience with panel, behavioral, consumer, or demographic data at scale
• Proven ability to effectively communicate complex technical details and concepts to external technical partners and clients