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    "requisitionDescription": "<div><div><div>Sequoia Financial Group is a growing Registered Investment Advisor (RIA), headquartered in Northeast Ohio, offering financial planning and wealth management services. At Sequoia, we exist with a singular purpose: to enrich lives. Our values define how we behave and guide us through the pursuit of our purpose to enrich lives. At Sequoia, our core values are:<br data-pasted=\"true\"><ul><ul><li><strong>Integrity.</strong>&nbsp; We act in the best interests of others by providing an honest, consistent experience for our clients and team.&nbsp;</li><li><strong>Passion</strong>. We pursue our full potential, seeking to continually enhance and evolve our ability to serve our clients and team.</li><li><strong>Teamwork.&nbsp;</strong>We subordinate our egos to work together for the benefit of our clients.&nbsp;</li></ul></ul>Our promise to team members is that you will grow with us. From experienced advisors to new college grads to transitioning principals, every team member will find Sequoia a place to refine their professional mission, move into new opportunities, go deeper, and lead further. We are built to help you build a career here as a long-term contributor in our work to enrich lives for generations.<h3 data-pasted=\"true\"><strong>Summary of the position:</strong></h3><p><span style=\"--original-color: #0e101a;color: #0e101a;\">As part of our expanding Data &amp; AI Office, we seek a highly motivated and hands-on&nbsp;</span><span style=\"--original-color: #0e101a;color: #0e101a;\">Data Scientist</span><span style=\"--original-color: #0e101a;color: #0e101a;\">&nbsp;to build intelligent models that drive personalization, operational efficiency, and strategic decision-making. This role is ideal for someone who thrives in experimentation, iterative development, and translating business needs into scalable data products.</span></p><p><span style=\"--original-color: #0e101a;color: #0e101a;\">The Data Scientist will develop product-ready models that support Sequoia&rsquo;s strategic initiatives in client experience, financial planning, operations, and marketing. This individual will work closely with business stakeholders to understand requirements, translate them into data science problems, and deliver actionable insights through robust modeling and experimentation.</span></p><p><span style=\"--original-color: #0e101a;color: #0e101a;\">This hands-on role requires technical depth in Python programming, data science workflows, and a strong understanding of mapping business requirements to data models. The ideal candidate will be highly innovative, comfortable with ambiguity, and eager to learn through experimentation and iteration.</span></p><p>This role reports directly to the Vice President of Data and Integrations and collaborates closely with the Data Architect, Client Experience, Marketing, and Technology teams.</p><h3><strong>Responsibilities</strong></h3><ul><li>Develop <span style=\"--original-color: #0e101a;color: #0e101a;\">and deploy predictive and descriptive models using Python and modern data science libraries</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Translate business requirements into data science problems and design appropriate modeling strategies</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Build product-ready models that can be integrated into client-facing and internal applications</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Conduct exploratory data analysis, feature engineering, and model validation</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Collaborate with stakeholders across departments to understand use cases and deliver insights</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Embrace iterative development, rapid prototyping, and continuous learning from experimentation</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Utilize coding accelerators and low-code tools where appropriate to speed up development</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Document modeling decisions, assumptions, and performance metrics for transparency and reproducibility</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Work with data engineers and architects to ensure models are scalable and maintainable in production</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Stay current with emerging techniques in machine learning, generative AI, and financial modeling</span></li></ul><h3><strong>Required Skills/Experience</strong></h3><ul><li>Master&rsquo;s Degree in Statistics</li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">1&ndash;2 years of experience in data science or machine learning roles</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Proficiency in Python and relevant libraries (e.g., pandas, scikit-learn, NumPy, matplotlib, seaborn)</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Strong understanding of statistical modeling, machine learning, and data preprocessing</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Demonstrated ability to map business requirements to data science solutions</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Experience with iterative development and rapid experimentation</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Familiarity with coding accelerators or low-code platforms (e.g., Azure ML Studio,&nbsp;</span><a href=\"http://H2O.ai\">H2O.ai</a><span style=\"--original-color: #0e101a;color: #0e101a;\">)</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Excellent communication skills and ability to present findings to non-technical stakeholders</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Strong documentation and organizational skills</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Experience in financial services, banking, or insurance sectors preferred</span></li></ul><h3><strong>Preferred Skills/Experience</strong></h3><ul><li>Exposure<span style=\"--original-color: #0e101a;color: #0e101a;\">&nbsp;to cloud-based data science environments (e.g., Azure ML, Databricks)</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Familiarity with tools such as Jupyter Notebooks, Git, and MLflow</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Experience working with Salesforce, Tamarac, eMoney, Fidelity, Schwab, and Box is a plus</span></li></ul><h3><strong>Competencies</strong></h3><ul><li>Highly <span style=\"--original-color: #0e101a;color: #0e101a;\">innovative and willing to challenge conventional approaches</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Comfortable learning from failed experiments and pivoting quickly</span></li><li><span style=\"--original-color: #0e101a;color: #0e101a;\">Ability to work independently and collaboratively in hybrid work settings</span></li></ul><p><span style=\"--original-color: #0e101a;color: #0e101a;\"><strong>If you are currently on a STEM OPT Visa that will eventually require sponsorship for the H1B Visa, unfortunately, we are not able to sponsor.</strong></span></p></div></div></div>\n",
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