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Head Of Data Jobs in Springfield, MA (NOW HIRING)

Director of Donor Relations

Deerfield, MA · On-site

$37.50 - $50.48/hr

Write, send, and track special acknowledgments from the Head of School and for memorial gifts ... Oversee the data integrity of donor naming opportunities * Assist the Deerfield Fund team and the ...

The Finance Business Partner will report to the Head of FP&A and will contribute to critical ... data is accurate and reconciles across various financial systems • Support monthly expense ...

New

VP, Workers Compensation

Glastonbury, CT · Hybrid

$194K - $308K/yr

Reporting Relationship Peter McCarron - SVP and Head of P&C Claims Skills, Knowledge & Abilities ... Advanced understanding and usage of data analytics tools. * Work well independently and as part of ...

Showing results 21-40

Head Of Data information

What does a head of data do?

A Head of Data is responsible for overseeing an organization's data strategy, including data governance, management, analytics, and security. They lead teams that collect, process, and analyze data to support business decision-making and drive growth. This role often involves collaborating with other departments to ensure data is utilized effectively and aligns with the company's objectives. Additionally, the Head of Data may set policies around data quality, compliance, and privacy, ensuring the organization meets regulatory requirements.

What are the key skills and qualifications needed to thrive as a head of data, and why are they important?

To thrive as a Head Of Data, you need deep expertise in data architecture, analytics, and strategy, usually supported by an advanced degree in a quantitative field and experience in data leadership roles. Proficiency with big data platforms (such as Hadoop or Spark), data visualization tools (like Tableau or Power BI), and knowledge of data governance frameworks are essential, with certifications in data management or cloud services (e.g., AWS, Azure) being advantageous. Strong leadership, communication, and stakeholder management skills help drive data initiatives and foster cross-functional collaboration. These skills are crucial for aligning data strategy with business goals, ensuring data quality, and empowering data-driven decision-making across the organization.

How does the head of data typically collaborate with other departments to drive data-driven decision making?

The Head of Data works closely with leaders from various departments—such as product, marketing, and operations—to identify business challenges and opportunities that can be addressed through data insights. They facilitate cross-functional meetings, translate business objectives into data strategies, and ensure that analytics and reporting align with organizational goals. Frequent collaboration also involves educating stakeholders on data literacy and advocating for best practices in data governance, ultimately fostering a culture where data informs key decisions.

What is the difference between Head Of Data vs Data Analyst?

AspectHead Of DataData Analyst
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's in relevant field; certifications like SQL, Excel, or Tableau beneficial
Work EnvironmentStrategic leadership, overseeing data teams, setting data strategyAnalyzing data sets, generating reports, supporting decision-making
Employer & Industry UsageUsed in organizations with large data teams across industriesCommon across industries for data-driven roles

The Head Of Data focuses on leading data strategy and managing data teams, while Data Analysts primarily analyze data and generate insights. Both roles require strong analytical skills, but the Head Of Data has a broader leadership and strategic responsibility.

What are the most commonly searched types of Of Data jobs in Springfield, MA? The most popular types of Of Data jobs in Springfield, MA are:
What are popular job titles related to Head Of Data jobs in Springfield, MA? For Head Of Data jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Head Of Data jobs in Springfield, MA look for? The top searched job categories for Head Of Data jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Head Of Data jobs? Cities near Springfield, MA with the most Head Of Data job openings:
Infographic showing various Head Of Data job openings in Springfield, MA as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 78% Physical, 2% Hybrid, and 20% Remote job distribution.

Principal AI Architect (Hartford)

AXA Group

Hartford, CT • On-site

Full-time

Posted 6 days ago


Job description

The Principal AI Architect to design and lead the technical strategy for our AI infrastructure, platforms, and systems. In this role, you will own the architectural vision for how we build, deploy, and scale AI solutions across the organization. You'll work at the intersection of AI/ML innovation, systems design, and engineering excellence, partnering with product, data science, and infrastructure teams to build robust, scalable, and responsible AI systems.

This is a high-impact technical leadership role ideal for someone who is passionate about AI systems, thinks deeply about architecture and design patterns, and is excited about solving complex technical challenges at scale.

Whatyou’ll be doing

What will your essential responsibilities include?

AI Architecture & Systems Design (40%)
  • Own the end-to-end technical architecture for AI systems, platforms, and infrastructure
  • Design scalable, modular, and extensible AI architectures that support multiple use cases
  • Define technical standards, best practices, and design patterns for AI development across the organization
  • Evaluate and recommend AI/ML frameworks, tools, and technologies (LLMs, vector databases, orchestration platforms, etc.)
  • Design solutions for complex challenges: model serving, real-time inference, batch processing, multi-model systems
  • Create architecture documentation, diagrams, and technical specifications for cross-functional teams
  • Conduct architecture reviews and provide technical guidance on design decisions
AI Infrastructure & Platform Development (25%)
  • Design and architect AI/ML platforms and infrastructure for scale (training, inference, monitoring, deployment)
  • Define MLOps and model lifecycle management practices (versioning, governance, lineage, reproducibility)
  • Design data pipelines, feature engineering infrastructure, and data management systems
  • Architect solutions for model serving, inference optimization, and latency requirements
  • Plan and execute infrastructure upgrades, migrations, and technical debt reduction
  • Establish monitoring, observability, and alerting frameworks for AI systems
  • Work with DevOps and Infrastructure teams to operationalize AI systems
AI/ML Innovation & Strategy (15%)
  • Stay at the forefront of AI/ML research and emerging technologies
  • Evaluate new models, frameworks, and techniques for strategic relevance and business impact
  • Design proof-of-concepts and pilots for emerging AI technologies (generative AI, multimodal models, agents, etc.)
  • Provide technical thought leadership on AI strategy and technologydmap
  • Mentor data scientists and engineers on architectural best practices and design patterns
  • Contribute to technical strategy discussions with product and business leadership
Technical Leadership & Collaboration (15%)
  • Lead and mentor senior engineers, architects, and technical leads
  • Establish technical vision and roadmap aligned with business objectives
  • Drive technical decision-making and architecture governance across AI teams
  • Partner with Product to translate business requirements into technical architecture
  • Collaborate with Data Science, Engineering, and Infrastructure teams on design and implementation
  • Lead design reviews, architecture discussions, and technical problem-solving sessions
  • Build and maintain robust relationships with key technical stakeholders
Responsible AI & Governance (5%)
  • Design systems and processes to ensure responsible AI practices (bias detection, fairness, explainability)
  • Establish governance frameworks for model performance, safety, and ethical deployment
  • Design monitoring and alerting for model drift, performance degradation, and fairness metrics
  • Navigate regulatory requirements and ensure compliance with AI regulations
  • Architect solutions for model interpretability, transparency, and auditability
  • Lead technical discussions on AI ethics, safety, and responsible system design

You will report to the Global Head of Digital Factory.

What you will BRING

We’re looking for someone who has these abilities and skills:

Required Skills and Abilities:
  • Extensive software engineering or systems architecture experience
  • Moderate hands‑on experience designing and building large‑scale AI/ML systems
  • Proven track record architecting systems that have been deployed to production at scale
  • Experience leading technical architecture decisions on complex, mission‑critical systems
  • Demonstrated expertise in distributed systems, scalability, and performance optimization
  • Deep expertise in AI/ML fundamentals, algorithms, and best practices
  • Outstanding understanding of modern ML frameworks and tools (TensorFlow, PyTorch, JAX, etc.)
  • Proficiency in at least one programming language (Python, Java, C++, Go, etc.)
  • Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
  • Robust understanding of data engineering, ETL pipelines, and data infrastructure
  • Knowledge of database systems, data warehousing, and query optimization
  • Familiarity with API design, microservices, and distributed system patterns
  • Strategic thinking with ability to balance innovation and pragmatism
  • Outstanding problem‑solving skills with ability to break down complex technical challenges
  • Excellent communication skills; ability to explain complex concepts clearly
  • Leadership presence and ability to influence technical teams and stakeholders
  • Intellectual curiosity and passion for staying current with AI/ML research and trends
  • Comfort with ambiguity and ability to make decisions with incomplete information
  • Robust judgment and ability to make sound architectural trade‑offs
  • Track record of mentoring senior engineers and technical leads
  • Experience navigating organizational and technical complexity at scale
  • Thought leadership in AI/ML architecture (speaking engagements, publications, open‑source contributions)
Desired Skills and Abilities:
  • Bachelor’s degree in Business, Computer Science, Project Management or a related field. Engineering, computer science, data science, or machine learning background
  • Understanding of AI infrastructure, model training, deployment, and MLOps
  • Familiarity with prompt engineering, fine‑tuning, and LLM customization
  • Knowledge of RAG (Retrieval‑Augmented Generation), agents, and advanced AI architectures
  • Experience in enterprise SaaS, B2B, or B2B2C product management
  • Track record in regulated industries (finance, healthcare, enterprise) or compliance‑heavy environments
  • Previous experience with platform or ecosystem products
  • Demonstrated understanding of AI safety, fairness, bias mitigation, governance and responsible AI frameworks
  • Knowledge of AI ethics principles and ability to operationalize them in product decisions
  • Experience with generative AI, LLMs, or conversational AI products
  • Experience with large language models (LLMs), transformers, and generative AI systems
  • Expertise in RAG (Retrieval‑Augmented Generation), fine‑tuning, and prompt engineering
  • Experience designing AI agents and multi‑step reasoning systems
  • Knowledge of model compression, quantization, and inference optimization
  • Familiarity with reinforcement learning or other advanced ML techniques
  • Experience designing and operating ML platforms (Kubeflow, MLflow, SageMaker, Vertex AI, etc.)
  • Expertise in model serving and inference optimization (TensorFlow Serving, Triton, etc.)
  • Experience with feature stores and feature engineering platforms
  • Knowledge of monitoring, observability, and alerting for ML systems
  • Experience with infrastructure‑as‑code and CI/CD pipelines for ML
Who WE are

AXA XL, the P&C and specialty risk division of AXA, is known for solving complex risks. For mid‑sized companies, multinationals and even some inspirational individuals we don’t just provide re/insurance, we reinvent it.

How? By combining a comprehensive and efficient capital platform, data‑driven insights, leading technology, and the best talent in an agile and inclusive workspace, empowered to deliver top client service across all our lines of business − property, casualty, professional, financial lines and specialty.

With an innovative and flexible approach to risk solutions, we partner with those who move the world forward.

Learn more at axaxl.com.

What we OFFER Inclusion

AXA XL is committed to equal employment opportunity and will consider applicants regardless of gender, sexual orientation, age, ethnicity and origins, marital status, religion, disability, or any other protected characteristic. At AXA XL, we know that an inclusive culture and enables business growth and is critical to our success. That’s why we have made a strategic commitment to attract, develop, advance and retain the most inclusive workforce possible, and create a culture where everyone can bring their full selves to work and reach their highest potential. It’s about helping one another — and our business — to move forward and succeed.

  • Five Business Resource Groups focused on gender, LGBTQ+, ethnicity and origins, disability and inclusion with 20 Chapters around the globe.
  • Robust support for Flexible Working Arrangements
  • Enhanced family‑friendly leave