Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Leads complex, cross-functional programs and projects spanning digital, data, AI, technology, operational, and enterprise capabilities. Responsibilities include integrated planning, budgeting, risk and issue management, stakeholder alignment, vendor coordination, governance, executive reporting, implementation readiness, documentation, deployment validation, and outcome tracking. The role also mentors project professionals and resolves complex delivery challenges across multiple teams and workstreams.

Leads PEMCO’s enterprise Project Management Office within Digital, AI & Technology. Responsibilities include managing the project portfolio, intake and prioritization, governance, reporting, capacity planning, delivery standards, risk escalation, and executive communications. The role leads and coaches Project and Program Managers, coordinates cross-functional stakeholders, supports quarterly planning, oversees vendor and budget coordination, develops portfolio metrics, and drives continuous PMO process improvement.

Performs property and casualty actuarial work across loss reserving, pricing, rate-making, predictive modeling, forecasting, regulatory filings, and product development. Analyzes trends, evaluates profitability and risks, supports product decisions, automates actuarial processes, and provides data-driven insights to business partners. The role requires strong mathematics, statistics, programming, insurance industry knowledge, and collaboration skills.

Leads integrated, lifecycle, customer journey, partner, and cross-channel marketing programs from strategy through execution and measurement. Develops campaigns across email, paid and digital media, social, websites, direct mail, and partner channels. Uses customer insights and performance data to optimize engagement, retention, renewal, cross-sell, and loyalty. Collaborates with cross-functional teams, agencies, and partners while managing timelines, KPIs, reporting, and executive presentations.

Develops and manages insurance product strategies to maximize customer value and profitable growth. Responsibilities include pricing analysis, regulatory filing strategy, product compliance, policy and coverage strategy, underwriting guidance, forecasting, budgeting, profit and loss management, and multi-year strategic planning. The role collaborates with cross-functional partners, mentors analysts, supervises employees, and leads product initiatives and business projects.

Leads product strategy and profitable growth for assigned insurance product lines. Responsibilities include managing profit and loss, forecasting, budgeting, pricing programs, statistical modeling, regulatory filing strategies, compliance, product plans, and cross-functional implementation. The role mentors product staff, influences senior stakeholders, analyzes markets and competitors, and represents company interests with leadership, government affairs, and industry partners.

The Principal Data Engineer designs and builds scalable cloud-native data platforms, pipelines, frameworks, and governed data products supporting analytics, reporting, AI, and operational workloads. Responsibilities include Databricks, Spark, Delta Lake, Azure, SQL Server, batch and streaming processing, data integration, performance optimization, governance, modernization, troubleshooting, architecture reviews, and mentorship. The role provides senior technical leadership without direct people management and supports insurance-domain data across policy, claims, billing, finance, and regulatory functions.

Leads the design, development, deployment, and monitoring of advanced statistical and machine learning models for insurance pricing, underwriting, claims, fraud, retention, and growth. Advises executives and actuarial teams, establishes modeling and experimentation standards, ensures responsible and scalable productionization, and mentors data scientists. The role also advances MLOps, AI infrastructure, model lifecycle management, explainability, fairness, and data science strategy.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

Serve as a liaison between business stakeholders and technical teams to elicit, document, and translate requirements; design and improve systems and processes; support implementations and post-release troubleshooting; mentor others; drive buy-vs-build decisions; facilitate training, data governance, and reporting needs; use Agile/Scrum/Waterfall methodologies and MS Copilot to create user stories and documentation while ensuring compliance with security and privacy requirements.