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Vice President Data Science Jobs (NOW HIRING)

Original Post Date: 4/3/2026 VP of Data Science Kaizen Analytix LLC, an analytics products and services company that gives clients unmatched speed to value through analytics solutions and actionable ...

The new VP must have a history of delivering high-quality work and building ongoing, trust-based ... Moreover, they should possess good knowledge of Data Science, Machine Learning, and Advanced ...

Job Summary The Vice President(VP), - Data Center Services(DCS) will play a key leadership role in ensuring the successful sourcing and delivery of complex infrastructure projects within the data ...

Vice President, Data Privacy At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the ...

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Vice President Data Science information

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$43.5K

$157.5K

$277.5K

How much do vice president data science jobs pay per year?

As of Jun 18, 2026, the average yearly pay for vice president data science in the United States is $157,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $190,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by a Vice President of Data Science when scaling data teams across an organization?

A Vice President of Data Science often encounters challenges such as aligning data initiatives with business objectives, ensuring consistent data governance practices, and fostering effective collaboration between technical and non-technical teams. Balancing the need for rapid innovation with maintaining data quality and compliance can also be demanding. Additionally, scaling the team requires strong leadership skills to recruit, mentor, and retain top talent while promoting a culture of knowledge sharing and continuous learning.

What is the difference between Vice President Data Science vs Data Scientist?

AspectVice President Data ScienceData Scientist
Required CredentialsAdvanced degrees (Master's/PhD), leadership experienceBachelor's or Master's in relevant field
Work EnvironmentExecutive leadership, strategic planningTechnical analysis, model development
Employer & Industry UsageCorporate, large organizations, tech, financeVaried industries, research labs, startups

The Vice President Data Science typically oversees data strategy and manages teams, requiring leadership and strategic skills. Data Scientists focus on building models and analyzing data. While both roles require strong technical skills, the VP role emphasizes management and vision, whereas Data Scientists are more hands-on with data analysis.

What are the key skills and qualifications needed to thrive as a Vice President of Data Science, and why are they important?

To thrive as a Vice President of Data Science, you need deep expertise in statistics, machine learning, and data analytics, typically supported by an advanced degree in a quantitative field and significant leadership experience. Familiarity with data platforms like Hadoop, Spark, and cloud-based analytics tools, as well as experience with programming languages such as Python or R, is crucial, along with certifications in data management or analytics. Strong strategic vision, communication, and team leadership skills distinguish top performers in this role. These skills and qualities drive innovation, enable data-driven decision-making, and ensure alignment with organizational goals.

What does a Vice President of Data Science do?

A Vice President of Data Science leads the data science division within an organization, overseeing teams that analyze large datasets to drive strategic business decisions. They are responsible for developing data-driven strategies, managing data science projects, and ensuring the alignment of analytics initiatives with the company’s goals. This executive role also involves collaborating with other leaders, mentoring data science teams, and staying updated on the latest technologies and trends in data science. Ultimately, the Vice President of Data Science ensures that the organization's data assets are leveraged to create measurable business value.

What Does a Vice President of Data Science Do?

As vice president of data science, your responsibilities include targeting audiences through both online and offline data. You lead a team of analysts, manage client needs, and implement solutions to build brands. Predictive analytics is a large part of this job, as is the ability to create strong content based on data science. You use analytical data to develop a business model that reaches a broader audience. Other duties include providing thought leadership, anticipating project risks, and translating analytical science into actionable marketing campaigns. This role is almost always in-house.

What cities are hiring for Vice President Data Science jobs? Cities with the most Vice President Data Science job openings:
What are the most commonly searched types of Data Science jobs? The most popular types of Data Science jobs are:
What states have the most Vice President Data Science jobs? States with the most job openings for Vice President Data Science jobs include:

Senior Vice President, Data Science Manager

BNY

Boston, MA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 15 days ago


Job description

BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.

We're seeking a future team member for the role of Data Science Manager, Revenue Analytics in Asset Servicing. This role is located in Boston.

BNY is seeking an SVP, Data Science Manager within Asset Servicing Deal Management and Controls to lead strategic initiatives at the intersection of data science, knowledge engineering, natural language processing, and applied AI. This role will focus on transforming how proposals, RFP, due diligence, and related controlled content is structured, governed, retrieved, and reused across Asset Servicing.

The successful candidate will lead the development of a governed, scalable content ecosystem that improves the quality, consistency, speed, and completeness of first-draft responses, while reducing manual effort and unnecessary subject matter expert outreach. This role combines data science leadership with a strong knowledge engineering focus, applying advanced analytical and AI methods to business text, response content, and approved firm artifacts to improve response generation, content quality, and operational efficiency.

This role will apply semantic search, sentence embeddings, similarity scoring, classification, clustering, duplicate detection, summarization, metadata tagging, named entity recognition, information extraction, answer recommendation, and content gap identification to improve knowledge reuse and proposal effectiveness.

Key Responsibilities:

Knowledge Engineering and Content Optimization

  • Lead the transformation of the Asset Servicing proposal knowledge base to improve first-draft quality, consistency, speed, and completeness across client opportunities.

  • Design scalable approaches to structure, govern, enrich, and optimize reusable proposal, due diligence, and controlled content, including Q&A pairs, reusable response modules, product descriptions, service language, and other approved firm artifacts.

  • Develop methods to organize content so it communicates technical, operational, product, service, risk, and control-related information clearly, accurately, and persuasively.

  • Establish content governance standards across taxonomy, ontology, metadata models, content schemas, lifecycle management, editorial quality, approvals, and version control.

  • Integrate and normalize diverse content sources into a unified, governed, and analytically manageable content ecosystem spanning structured and unstructured text assets.

Applied AI, NLP, and Retrieval Intelligence

  • Apply advanced NLP, text analytics, machine learning, and AI methods to improve response drafting, semantic retrieval, content reuse, and language quality.

  • Develop approaches using semantic search, sentence embeddings, similarity scoring, document classification, clustering, duplicate detection, topic extraction, summarization, metadata tagging, named entity recognition, and information extraction.

  • Build scoring, ranking, and answer recommendation frameworks to identify the most relevant, current, high-quality, and reusable content for specific proposal and due diligence use cases.

  • Create frameworks to evaluate and improve multiple forms of business language, including technical explanatory content, service model descriptions, control and risk language, product capability statements, proof points, differentiators, and persuasive client-facing messaging.

  • Support AI-enabled drafting workflows through retrieval-augmented generation concepts, prompt design, response evaluation, and human-in-the-loop review approaches aligned with responsible AI practices.

Strategic Partnership and Execution

  • Partner with sales, product, solutions, deal management, controls, and subject matter experts to improve the sourcing, validation, prioritization, maintenance, and reuse of high-value content.

  • Reduce redundant SME outreach by identifying content gaps, extracting reusable knowledge from expert contributions, and converting that knowledge into governed response assets.

  • Lead and execute high-impact initiatives across knowledge engineering, NLP, retrieval, and AI-enabled content optimization, from problem definition through delivery.

  • Define project scope, milestones, deliverables, and operating cadence for strategic workstreams.

  • Translate analytical findings into actionable recommendations for business leaders and stakeholders.

Innovation, Measurement, and Business Impact

  • Advance the use of AI, NLP, language quality analytics, and content intelligence to support proposal excellence and sales enablement across Asset Servicing.

  • Analyze workflow bottlenecks, content usage patterns, response quality, content freshness, expert dependency, and operational inefficiencies to improve proposal cycle times and first-draft effectiveness.

  • Define and apply performance metrics such as reuse rates, answer acceptance, first-draft quality, manual edit rates, SME touch frequency, and cycle-time reduction.

  • Support a "One Asset Servicing" and "One BNY" approach through a unified, AI-enabled content strategy.

  • Identify opportunities to improve the proposal development lifecycle through innovations in knowledge engineering, enterprise retrieval, and language AI.

Qualifications:

Required

  • Bachelor's degree or equivalent work experience with experience preferred in related fields.

  • Extensive experience in data science, NLP, text analytics, knowledge engineering, knowledge management, content operations, proposal enablement, sales analytics, or related strategic and analytical roles.

  • Strong experience working with large-scale unstructured text data, document-centric repositories, and enterprise content libraries.

  • Demonstrated expertise in NLP and language-focused machine learning techniques such as semantic search, sentence embeddings, similarity scoring, classification, clustering, duplicate detection, topic extraction, summarization, named entity recognition, and information extraction.

  • Experience designing analytical or AI-driven solutions for content that must balance technical accuracy, control sensitivity, regulatory or service-related precision, and clear client-facing communication.

  • Strong understanding of language quality dimensions such as factual consistency, technical precision, clarity, readability, tone, relevance, persuasiveness, and alignment to approved messaging.

  • Experience building scoring, ranking, recommendation, or retrieval frameworks for business text based on relevance, freshness, quality, specificity, strategic alignment, and reusability.

  • Experience designing taxonomies, ontologies, metadata models, and content schemas for enterprise content organization, retrieval, analytics, and governance.

  • Proficiency in Python and relevant data science and NLP libraries such as pandas, NumPy, scikit-learn, spaCy, NLTK, transformers, sentence-transformers, and related frameworks.

  • Strong SQL skills and familiarity with data engineering concepts supporting text-centric workflows, corpus management, feature generation, and integration of structured and unstructured data sources.

  • Experience with large language models, prompt design, response evaluation, retrieval-augmented generation concepts, human-in-the-loop review, and responsible AI practices in enterprise settings.

  • Demonstrated ability to operate effectively in a hands-on leadership role, balancing strategic direction, stakeholder engagement, and direct execution.

  • Ability to work effectively across technical, product, control, risk, and commercial business domains.

  • Effective communication, editorial judgment, and stakeholder management skills.

  • High proficiency in Excel, PowerPoint, and Word.

Preferred

  • Master's degree in data science, computer science, computational linguistics, information science, applied mathematics, knowledge systems, business analytics, or a related technical field.

  • 10+ years of relevant work experience.

  • Asset Servicing industry knowledge and experience.

  • Experience in Deal Management, controls architecture, product management, proposal management, sales enablement, due diligence content, or consulting environments.

At BNY, our culture allows us to run our company better and enables employees' growth and success. As a leading global financial services company at the heart of the global financial system, we influence nearly 20% of the world's investible assets. Every day, our teams harness cutting-edge AI and breakthrough technologies to collaborate with clients, driving transformative solutions that redefine industries and uplift communities worldwide.

Recognized as a top destination for innovators, BNY is where bold ideas meet advanced technology and exceptional talent. Together, we power the future of finance - and this is what #LifeAtBNY is all about. Join us and be part of something extraordinary.

At BNY, our culture speaks for itself, check out the latest BNY news at BNY Newsroom & BNY LinkedIn

 Here's a few of our recent awards:

  • America's Most Innovative Companies, Fortune, 2025
  • World's Most Admired Companies, Fortune 2025
  • "Most Just Companies", Just Capital and CNBC, 2025

    Our Benefits and Rewards:

    BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy. We provide access to flexible global resources and tools for your life's journey. Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.

    BNY is an Equal Employment Opportunity/Affirmative Action Employer - Underrepresented racial and ethnic groups/Females/Individuals with Disabilities/Protected Veterans.

    BNY assesses market data to ensure a competitive compensation package for our employees. The expected base salary for this position when employment commences can be found in the Job Info section at the bottom of the posting. 

    Base salary offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Base salary is only part of the total rewards package, which may include eligibility for an annual discretionary incentive award. Subject to the terms and conditions of the applicable plans then in effect, eligible employees may enroll in a 401(k) plan as well as participate in Company-sponsored medical, dental, vision, and basic life insurance plans for the employee and the employee's eligible dependents. Eligible employees also may receive other benefits (including various paid time off benefits, such as vacation and sick time), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

    If hired, the employee will be in an "at will" position and the Company reserves the right to modify base salary (as well as any other discretionary payments or compensation programs) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.