Senior Data Scientist

Sequoia Financial Group Llc • Mayfield Heights, OH

5d • Onsite

About The Position

Sequoia Financial Group is seeking a highly motivated and hands-on Sr. Data Scientist to join their expanding Data & AI Office. This role is designed for an individual who excels in experimentation, iterative development, and building new capabilities from the ground up. The successful candidate will be comfortable with overlapping responsibilities in data engineering, data science, and solution development within an evolving environment. The Sr. Data Scientist will create product-ready models to support Sequoia’s strategic goals in client experience, financial planning, operations, and marketing. This involves collaborating with business stakeholders to understand needs, define data science problems, and deliver actionable insights through robust modeling and experimentation. Unlike traditional roles, this position requires a builder mindset, contributing to the data environment while developing analytical solutions. The role demands technical depth in Python, data science workflows, and the ability to translate business needs into data models. Innovation, comfort with ambiguity, and a learning-through-experimentation approach are key. Success requires operating across data science, data engineering, and solution development, helping to build the foundation of Sequoia’s AI and Data capabilities. This is not a narrowly defined role within a mature analytics organization. The position reports to the Vice President of Data and Integrations and collaborates with Data Architect, Client Experience, Marketing, and Technology teams.

Requirements

• Bachelor’s degree from an accredited US college or university in Statistics, Data Science, Computer Science, Mathematics, Engineering or a related field is required
• 7- 8+ years of experience in data science, machine learning, analytics, data engineering, or related technical roles
• Proficiency in Python and relevant libraries (e.g., pandas, scikit-learn, NumPy, matplotlib, seaborn)
• Strong understanding of statistical modeling, machine learning, and data preprocessing
• Demonstrated ability to map business requirements to data science solutions
• Experience with iterative development and rapid experimentation
• Familiarity with coding accelerators or low-code platforms (e.g., Azure ML Studio, H2O.ai)
• Excellent communication skills and ability to present findings to non-technical stakeholders
• Strong documentation and organizational skills
• Demonstrated ability to operate effectively with limited structure and evolving requirements
• Familiarity with cloud data platforms, data pipelines, and analytics infrastructure
• Experience working across both data science and data engineering disciplines preferred
• Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence or continue employment at any point in time.

Nice To Haves

• Master’s degree in Statistics, Data Science or Computer Science is strongly preferred
• Experience in financial services, banking, or insurance sectors preferred
• Exposure to cloud-based data science environments (e.g., Azure ML, Databricks)
• Familiarity with tools such as Jupyter Notebooks, Git, and MLflow
• Experience working with Salesforce, Tamarac, eMoney, Fidelity, Schwab, and Box is a plus
• Experience working in startup, consulting, high-growth, or rapidly evolving environments
• Experience helping build data platforms, analytics environments, or AI capabilities from early-stage maturity
• Experience partnering with business and technical stakeholders to define requirements in ambiguous environments

Responsibilities

• Develop and deploy predictive and descriptive models using Python and modern data science libraries
• Translate business requirements into data science problems and design appropriate modeling strategies
• Build product-ready models that can be integrated into client-facing and internal applications
• Conduct exploratory data analysis, feature engineering, and model validation
• Collaborate with stakeholders across departments to understand use cases and deliver insights
• Embrace iterative development, rapid prototyping, and continuous learning from experimentation
• Utilize coding accelerators and low-code tools where appropriate to speed up development
• Document modeling decisions, assumptions, and performance metrics for transparency and reproducibility
• Work with data engineers and architects to ensure models are scalable and maintainable in production
• Stay current with emerging techniques in machine learning, generative AI, and financial modeling
• Partner with data engineering resources to help define, validate, and operationalize data pipelines, data models, and analytics-ready datasets
• Contribute to the development and evolution of Sequoia’s cloud data and analytics environment
• Operate effectively in a rapidly evolving AI and data organization where priorities and requirements may change as new opportunities emerge
• Identify gaps in data, infrastructure, and processes and proactively recommend solutions
• Balance immediate business needs with long-term platform and analytics objectives

Benefits

• Sequoia a place to refine their professional mission, move into new opportunities, go deeper, and lead further.
• Sequoia is an equal opportunity employer.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior