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Data Scientist

Оценка ИИ

Отличная вакансия с высокой и прозрачной заработной платой для специалиста с опытом от 3 лет. Компания работает на острие технологий, внедряя LLM в финансовый сектор, что обеспечивает профессиональный рост.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Средне-высокий уровень сложности обусловлен необходимостью сочетать глубокие знания в области финансов (портфельное управление, риск-моделирование) с современным стеком ИИ, включая LLM и RAG. Требуется опыт работы со Snowflake и умение взаимодействовать с бизнес-стейкхолдерами.

Анализ зарплаты

Медиана155 000 $
Рынок130 000 $ – 190 000 $
Оценка ИИ

Предлагаемый диапазон $180,000–$240,000 значительно выше среднего по рынку для Data Scientist с опытом около 3 лет, даже для таких дорогих локаций, как Нью-Йорк или Бостон. Это соответствует уровню Senior или узкоспециализированного эксперта в FinTech.

Сопроводительное письмо

I am writing to express my strong interest in the Data Scientist position at Focus Financial Partners. With over three years of experience in data science and a deep background in financial analytics, I am excited about the opportunity to apply my skills in predictive modeling and machine learning to enhance your wealth management platform. My expertise in Python, SQL, and Snowflake, combined with a solid understanding of portfolio construction and risk modeling, aligns perfectly with the requirements of this role.

Furthermore, I have been actively working with modern LLMs and RAG architectures, including OpenAI function calling and vector databases. I am particularly drawn to Focus Financial Partners because of your commitment to a client-first fiduciary philosophy and your forward-thinking approach to integrating AI into core financial workflows. I am confident that my technical proficiency and ability to translate complex data into actionable business insights will make me a valuable asset to your technology team.

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Откликнитесь в focusfinancialpartners уже сейчас

Присоединяйтесь к лидеру в сфере управления капиталом и внедряйте передовые LLM-решения в финансовую аналитику!

Описание вакансии

Position Summary

We are seeking a highly capable Data Scientist with approximately three years of experience to accelerate our journey toward data-driven wealth management. In this role, you will partner closely with advisors, investment professionals, and technology teams to unlock insights that enhance portfolio construction, client personalization, and operational performance. This position blends financial domain knowledge with advanced analytics and machine learning, offering an opportunity to influence the evolution of our data ecosystem and the future of our platform.

This role can be located in St. Louis, MO, Boston, MA or New York, NY.

Primary Responsibilities

  • Analyze large, complex financial and client datasets to uncover trends, behavioral patterns, and investment signals.
  • Design, validate, and operationalize predictive models to support asset allocation, risk assessment, and client segmentation strategies.
  • Collaborate with business and financial stakeholders to translate strategic objectives into analytical approaches and data-driven solutions.
  • Build and maintain scalable data pipelines and workflows, ensuring reliable data ingestion, transformation, and quality within Snowflake environments.
  • Develop intuitive dashboards, visualizations, and reporting artifacts (Power BI, Tableau, or similar) to communicate insights and influence decision-making.
  • Work closely with engineering teams to integrate analytical outputs and models directly into core wealth management systems and workflows.
  • Maintain thorough documentation and uphold data governance, controls, and compliance standards aligned with financial regulations and industry best practices.

Qualifications

  • Master’s degree in Data Science, Computer Science, Statistics, Finance, or a related quantitative field.
  • 3+ years of hands-on experience in Data Science, ideally within financial services, wealth management, investment analytics, or related sectors.
  • Strong programming experience in Python or R for statistical modeling, machine learning, and data manipulation.
  • Proficiency in SQL and demonstrated experience with Snowflake for data warehousing and analytical workloads.
  • Solid understanding of financial instruments, portfolio construction, performance metrics, and risk modeling concepts.
  • Experience with data visualization and business intelligence platforms (e.g., Tableau, Power BI, Looker).
  • Familiarity with cloud environments (AWS, Azure, or GCP) and modern data stack components.
  • Exceptional communication and stakeholder engagement skills, with the ability to convey complex concepts to non-technical audiences.
  • Experience with OpenAI function calling, MCP servers, or custom agent integration
  • Experience with Retrieval-Augmented Generation (RAG) and vector database expertise
  • Experience working with modern LLMs (OpenAI, Anthropic, Google)

#LI-KJ2

This is an exempt position. The annualized base pay range for this role is expected to be between $180,000-$240,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate’s experience and education.

About Focus Financial Partners

Focus is a leading financial services firm comprised of integrated wealth management, family office, and business management services. Blending deep expertise and expansive resources with a boutique, client-first fiduciary philosophy, Focus helps individuals, families, and institutions navigate complex financial situations with highly personalized solutions tailored to their unique needs. To learn more about Focus, visit www.focusfinancialpartners.com or follow the company on LinkedIn.

Focus is an equal opportunity employer and bases its employment decisions on the employee or candidate’s skillset, and without regard to an employee or candidate’s race, color, religion, sex (including pregnancy), gender identity, sexual orientation, national origin, age, disability, genetic information, veteran status, or any other characteristic protected by local, state and/or federal law. 

Focus complies with federal and state disability laws and makes reasonable accommodations for applicants and employees with disabilities. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact careers@focuspartners.com.

*The following language is for US based roles only*

For California Applicants:Information on your California privacy rights can be found here

For Indiana Applicants: It is unlawful for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.

For Maryland Applicants: I UNDERSTAND THAT UNDER MARYLAND LAW, AN EMPLOYER MAY NOT REQUIRE OR DEMAND, AS A CONDITION OF EMPLOYMENT, PROSPECTIVE EMPLOYMENT OR CONTINUED EMPLOYMENT, THAT ANY INDIVIDUAL SUBMIT TO OR TAKE A POLYGRAP OR SIMILAR TEST.  AN EMPLOYER WHO VIOLATES THIS LAW IS GUILTY OF A MISDEMEANOR AND SUBJECT TO A FINE NOT EXCEEDING $100. 

For Massachusetts Applicants: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.  An employer who violates this shall be subject to criminal penalties and civil liability. 

For Montana Applicants: If hired, the employment relationship is governed by the Wrongful Discharge from Employment Act. Mont. Code Ann. Section 39-2-901.

For Rhode Island Applicants: Focus is subject to Chapters 29-38 of Title 28 of the General Laws of Rhode Island and is therefore covered by the state’s workers’ compensation law. If you willfully provide false information about your ability to perform the essential functions of the job, with or without reasonable accommodations, you may be barred from filing a claim under the provisions of the Workers’ Compensation Act of the State of Rhode Island if the false information is directly related to the personal injury that is the basis for the new claim for compensation.  The Company complies fully with the Americans with Disabilities Act.

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Создайте идеальное резюме с помощью ИИ-агента

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Навыки

  • Python
  • R
  • SQL
  • Snowflake
  • Machine Learning
  • Power BI
  • Tableau
  • Looker
  • AWS
  • Azure
  • GCP
  • OpenAI
  • Large Language Models
  • Retrieval-Augmented Generation
  • Vector Databases
  • Statistics
  • Financial Modeling

Возможные вопросы на собеседовании

Вакансия требует понимания финансовых инструментов и риск-моделирования.

Как бы вы подошли к созданию модели оценки риска для диверсифицированного инвестиционного портфеля, используя имеющиеся у нас данные Snowflake?

В описании указаны LLM, RAG и OpenAI function calling.

Опишите ваш опыт внедрения систем Retrieval-Augmented Generation (RAG). С какими основными проблемами качества ответов вы сталкивались и как их решали?

Роль предполагает работу с большими данными в среде Snowflake.

Расскажите о наиболее сложном SQL-запросе или конвейере данных, который вы оптимизировали для повышения производительности аналитики.

Важно умение объяснять сложные вещи простыми словами.

Как вы объясните нетехническому финансовому консультанту, почему модель машинного обучения приняла именно такое решение по сегментации клиентов?

Упоминается интеграция моделей в основные системы управления капиталом.

Каков ваш опыт в операционализации (MLOps) моделей? Как вы обеспечиваете надежность и мониторинг моделей после их внедрения в продакшн?

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