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Vice President Data Scientist Deep Learning Jobs

Updater

VP, Data

... deep historical analysis. • Build and scale a high-performing data engineering organization ... learning as well as LLM-based models • Experience designing systems that accommodate ambiguity ...

OptimizeRx

Vice President, Data and Analytics Products

$200K - $220K/yr

The ideal candidate combines strategic product leadership with deep experience commercializing data ... Science, and AI teams to transform advanced analytics, predictive models, and machine learning ...

Lyra Health

VP of Data and AI

$251K - $346K/yr

Required Experience * 10+ years of progressive experience in AI, machine learning, data science ... Deep expertise in modern data architecture, cloud-based data platforms (ideally AWS), data ...

Lyra Health

VP of Data and AI

Charleston, WV · Remote

$251K - $346K/yr

Required Experience * 10+ years of progressive experience in AI, machine learning, data science ... Deep expertise in modern data architecture, cloud-based data platforms (ideally AWS), data ...

Five9

Vice President, Data Science

San Ramon, CA

Deep Expertise in Modern AI/ML * Extensive hands-on experience with LLMs, agentic architectures ... Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Applied ...

Trella Health

Build and scale the organization's AI/ML capabilities, including traditional ML, deep learning, NLP ... Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or related field ...

The Knot Worldwide

VP, Data Science

$235K - $336K/yr

We're united by authentic connection, shared purpose, and a deep commitment to the global community ... The VP of Data Science & Analytics will lead experimentation, business intelligence, and advanced ...

Five9

Vice President, Data Science

Deep Expertise in Modern AI/ML * Extensive hands-on experience with LLMs, agentic architectures ... Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Applied ...

Five9

OR

Deep Expertise in Modern AI/ML * Extensive hands-on experience with LLMs, agentic architectures ... Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Applied ...

Centerline

Vice President Data Center

Richmond, VA · On-site +1

The ideal candidate will have deep experience in Critical Infrastructure/Data Center construction ... The VP of DCS, will serve as the key liaison between internal teams and external stakeholders ...

Vibrant

Assistant Vice President, Data

New York, NY · On-site

$180K - $200K/yr

The Assistant Vice President, Data is a senior enterprise data leadership role within Vibrant ... Strong command of data science and machine learning:proficiencyin Python-based ML ecosystems ...

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How much do vice president data scientist deep learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for vice president data scientist deep learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.
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Vice President Data Scientist Deep Learning jobs near you

VP, Data

Updater

Remote

Full-time

Re-posted 17 days ago

Job description

Job Summary:
Updater is a leading technology platform focused on enhancing customer acquisition and retention through intelligent systems. They are seeking a VP of Data to elevate data-driven decision-making across the company, architecting systems that transform fragmented signals into reliable intelligence while managing a high-performing data engineering team.
Responsibilities:
• Own the long-term data strategy in partnership with Engineering, Finance, Product, and Executive Leadership.
• Define and evolve the end-to-end data architecture across acquisition, transactions, fulfillment, revenue recognition, and lifecycle events.
• Design scalable, auditable systems that accurately model complex, multi-role KPIs while balancing speed, accuracy, and cost.
• Build data systems that accurately models affiliate revenue-share agreements, confirmations, cancellations, and adjustments.
• Enable early detection of fraud and performance anomalies before they materially impact margin.
• Partner with Finance and cross-functional leaders to establish canonical revenue metrics and shared KPI definitions.
• Reduce the latency between business events and actionable insight.
• Enable faster experimentation, channel optimization, and partner performance analysis through reliable pipelines and tooling that support both real-time visibility and deep historical analysis.
• Build and scale a high-performing data engineering organization grounded in technical excellence, data quality, and operational rigor.
• Foster a collaborative, high-ownership culture that empowers teams to do their best work, operate effectively in ambiguity, and deliver durable systems that accelerate business impact.
• Translate business ambiguity into technical clarity — and technical complexity into business understanding.
• Clearly articulate data definitions, tradeoffs, and system constraints.
• Serve as a trusted partner to Product, Engineering, Finance, and Executive Leadership in driving high-impact decisions.
Qualifications:
Required:
• 10+ years of experience in data engineering or data platform leadership, including prior VP / Head of Data Engineering scope (or equivalent)
• Proven ownership of data systems directly tied to revenue, billing, or financial outcomes
• Deep expertise in modern data architectures (batch + streaming, warehouses, orchestration, modeling)
• Comfortable doing vendor evaluations, build vs buy decisions, and success implementing infrastructure projects.
• Strong command of data quality, lineage, observability, and governance — with pragmatic execution
• Experience stewarding data lifecycle with ML models, both traditional supervised learning as well as LLM-based models
• Experience designing systems that accommodate ambiguity, delayed signals, and evolving business rules
• Ability to drive clarity and alignment where metrics are contested and incentives may compete
• Strong understanding of attribution, leading vs. lagging indicators, and decision-enabling data principles
• Clear judgment that timely, decision-enabling truth is more valuable than theoretical perfection
Preferred:
• Experience in affiliate marketing, marketplaces, fintech, adtech, or other revenue-complex environments strongly preferred
Company:
Embedded commerce for essential home services. Founded in 2011, the company is headquartered in New York, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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