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Avp Data Science Jobs (NOW HIRING)

AVP Data Science - GD05AE We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to ...

AVP, Data Solutions Engineering

Jersey City, NJ · Hybrid

$119K - $143K/yr

Deliver well-architected data solutions in partnership with data platform engineers, data governance, data science, and data analytics/visualization peers. * Partner with business teams to design ...

Minimum of four (4) years of work experience in a data analyst, data science, or data engineering role, including direct experience in technical product management and/or data analysis activities ...

AVP, Data Solutions Engineering

Jersey City, NJ · Hybrid

$119K - $143K/yr

Deliver well-architected data solutions in partnership with data platform engineers, data governance, data science, and data analytics/visualization peers. * Partner with business teams to design ...

Minimum of four (4) years of work experience in a data analyst, data science, or data engineering role, including direct experience in technical product management and/or data analysis activities ...

Minimum of four (4) years of work experience in a data analyst, data science, or data engineering role, including direct experience in technical product management and/or data analysis activities ...

The candidate should have 7+ years of industry experience in data science and analytics. Graduate degrees in a technical field such as Statistics, Computer Science, Data Science, Bioinformatics ...

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Avp Data Science information

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$37.5K

$122.7K

$196.5K

How much do avp data science jobs pay per year?

As of Jul 8, 2026, the average yearly pay for avp data science 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.

What are some common challenges faced by an AVP of Data Science when aligning data initiatives with business goals?

As an AVP of Data Science, one of the key challenges is ensuring that complex data projects remain closely aligned with evolving business objectives. Balancing technical innovation with practical, actionable outcomes often requires clear communication between data teams and business stakeholders. Navigating organizational silos, managing competing priorities, and translating analytical findings into business impact are critical components of the role. Successful AVPs frequently foster cross-functional collaboration and maintain a strategic perspective to maximize the value of data-driven initiatives.

What does an AVP of Data Science do?

An AVP (Assistant Vice President) of Data Science leads data science teams and projects within an organization, typically overseeing the development of data-driven solutions to support business objectives. They are responsible for setting the strategy for data analysis, managing team members, collaborating with stakeholders, and ensuring high-quality delivery of analytics and machine learning initiatives. The AVP also plays a key role in identifying opportunities to leverage data for business growth, implementing best practices, and staying updated on the latest technologies in data science.

What is an AVP in data science?

An AVP (Assistant Vice President) in data science is a senior leadership role responsible for overseeing data projects, developing strategies, and managing teams of data scientists and analysts. The position often requires strong technical skills, experience with data tools like Python or R, and leadership abilities to align data initiatives with business goals.

What is the salary of AVP data scientist?

The salary for an AVP Data Scientist at JP Morgan typically ranges from $120,000 to $160,000 annually, depending on experience, location, and specific team. Additional compensation may include bonuses and benefits, and the role often requires proficiency in data analysis tools and programming languages like Python or R.

What is the difference between Avp Data Science vs Data Scientist?

AspectAvp Data ScienceData Scientist
Required CredentialsAdvanced degree (Master's/PhD), experience in leadership rolesBachelor's or Master's in relevant field, some experience
Work EnvironmentStrategic, managerial, cross-departmental collaborationHands-on data analysis, model development, coding
Employer & Industry UsageFinancial services, tech, consulting firms, often in leadershipTech companies, startups, research institutions
Common Search & ComparisonHigher-level strategic role, leadership focusTechnical, analytical role, implementation focus

In summary, an Avp Data Science typically holds a senior leadership position with strategic responsibilities and requires advanced credentials, whereas a Data Scientist is more focused on technical analysis and model development. The roles differ mainly in scope, experience, and level of responsibility within organizations.

What are the key skills and qualifications needed to thrive as an AVP Data Science, and why are they important?

To thrive as an AVP Data Science, you need advanced expertise in statistics, machine learning, and data analysis, typically supported by a master’s or PhD in a quantitative field and several years of relevant experience. Familiarity with programming languages like Python or R, big data platforms (e.g., Hadoop, Spark), and experience with data visualization tools and cloud technologies are commonly required. Strong leadership, strategic thinking, and communication skills set top candidates apart by enabling them to guide teams and explain complex findings to stakeholders. These skills and qualities are crucial for driving data-driven decision-making and delivering business value through analytics.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or data subsets to improve model performance efficiently.
More about Avp Data Science jobs
What cities are hiring for Avp Data Science jobs? Cities with the most Avp Data Science job openings:
What states have the most Avp Data Science jobs? States with the most job openings for Avp Data Science jobs include:
AVP Applied AI, Claims

AVP Applied AI, Claims

The Hartford

Hartford, CT • Hybrid

Full-time

Re-posted 10 days ago


The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 109 frontline employees who took The Breakroom Quiz

51st of 278 rated insurance


Job description

AVP Data Science - GD05AE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford is hiring an AVP leading Applied AI for the Claims organization. This leader will play a pivotal role in transforming the end-to-end Claims process by developing and embedding AI capabilities to enhance outcomes, process and experience.

This role will have aHybrid work schedule,with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week. Candidates must be eligible to work in the US without company sponsorship.

Primary Job Responsibilities

  • Own delivery, performance, and risk outcomes for a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams; translate Claims and enterprise AI priorities into a multi-year roadmap and investment plan.
  • Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions (e.g., forecasting, triage, recommendations, anomaly/fraud detection, RAG/assistants, and agentic workflow orchestration).
  • Be the senior business partner for Claims leaders: proactively understand short- and long-term goals, shape the problem statements, define success measures, and ensure solutions are adopted and embedded into core claim processes and colleague experiences.
  • Build deep partnerships within portfolio and value stream frameworks; promote agile, iterative delivery through cross-functional teams to ensure fit-for-purpose solutions and rapid learning cycles.
  • Lead and develop senior leaders and teams (e.g., asset owners, data engineers, data scientists, ML engineers), building bench strength through succession planning, coaching, and capability development while creating an engaged and inclusive culture
  • Provide portfolio-level technical direction and oversight, partnering with Principal Individual Contributors, Architecture, AI Platform, and Centers of Excellence to drive consistent adoption of approved standards, patterns, and guardrails
  • Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk-especially for GenAI and agentic solutions operating in claims environments.
  • Establish and enforce evaluation, monitoring, and production readiness across solution types (classification, regression, retrieval/RAG/chat, forecasting), including metric taxonomies, thresholds, validation evidence, gold/synthetic test sets, A/B testing, drift detection, failure mode analysis, and incident response expectations.
  • Set governance expectations for unstructured data and retrieval across Claims (document ingestion, parsing/OCR, layout-aware extraction, metadata/lineage, access controls, PII detection/redaction, auditability), including embedding/retrieval strategies and grounding validation aligned to enterprise standards.
  • Accountable for AI governance and compliance-by-design across the Claims portfolio, partnering with Legal, Compliance, Model Risk, Privacy, Security, and Audit; maintain audit readiness with clear controls, artifacts, escalation paths, and operational evidence.
  • Influence technology integration and platform strategy by partnering with Technology, Data, AI Platform, AI/MLOps, and Architecture teams on tooling, standard work, reusable capabilities, and scalable patterns for Predictive, Generative, and Agentic AI.
  • Champion reuse and scalability by partnering with AI platform owners and peers to develop and integrate reusable Claims AI capabilities within The Hartford's AI platform.
  • Provide thought leadership and change leadership: educate stakeholders, identify new AI opportunities, advance a data-driven culture, and drive change to core Claims processes through innovative quantitative/AI techniques.
  • Oversee portfolio planning, dependencies, resourcing, and financial stewardship, adapting to changing priorities, capacity constraints, technical risks, and regulatory needs while driving continuous improvement in delivery effectiveness and value realization.
  • Maintain strong knowledge of business processes and data sources and stay current on advancements in Machine Learning, GenAI/agentic frameworks, evaluation/guardrails, MLOps, cloud engineering, and emerging technologies.

Skills & Leadership Capabilities

  • Demonstrated experience leading large, complex Applied AI portfolios in regulated enterprise environments with consistent delivery discipline and risk management.
  • Strong business partnership and influence skills-able to translate Claims objectives into AI product strategy/roadmaps and drive adoption through operating model alignment and stakeholder engagement.
  • Deep technical fluency across Predictive ML + Generative + Agentic AI, including prompt engineering, RAG, agentic frameworks, evaluation methods, guardrail management, and AI/MLOps/model lifecycle management.
  • Strong governance and responsible AI grounding: model risk management, fairness/safety, explainability, monitoring, and compliance-by-design.
  • Applied understanding of unstructured data and retrieval systems (document ingestion pipelines, OCR, layout-aware extraction, embeddings, hybrid/dense retrieval, reranking, metadata/lineage, PII controls).
  • Proven ability to build and grow high-performing technical teams and establish operating rhythms across multiple teams/value streams.
  • Exceptional communication skills-able to communicate effectively at all levels and convert complex technical trade-offs into clear business implications and decisions.
  • Strong strategic thinking, analytical capability, negotiation/influence, conflict resolution, and ability to work autonomously across multiple priorities.

Education & Experience

  • 12+ years of applicable experience in Data Science, Applied AI, Analytics, Machine Learning Engineering, or related fields, including building and scaling AI solutions in production.
  • 7+ years of formal people leadership experience (leading leaders and/or multi-team organizations.
  • Insurance and/or Claims domain experience strongly preferred, with demonstrated success driving AI-enabled process transformation.
  • Bachelor's degree required; Master's or Ph.D. preferred in Machine Learning, Data Science, Computer Science, Applied Mathematics, or similar analytical field.
  • Proficiency with cloud platforms (preferably AWS or GCP) and their AI/ML ecosystems.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$182,400 - $273,600

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us|Our Culture|What It's Like to Work Here|Perks & Benefits


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About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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