• Define and present comprehensive Dell solutions to customers, showcasing products and services, and assist sales staff in identifying potential applications to meet customer needs. • Conduct customer needs analysis and prepare detailed product specifications to support high-end product and solution sales. • Scope projects and coordinate internal specialists and cross-department activities. • Assist sellers in creating demand for products, leveraging a high degree of technical competency to engage with technical users and buyers. • Deliver high-impact presentations at client sites and support complex accounts. • Build and manage relationships with technical teams and IT leaders; assess and validate approaches to selling enterprise/client products and services. • Ensure operability of complex product and service configurations within customer environments. • Analyze and apply industry and market knowledge to articulate the value of solutions, including competitor strengths and vulnerabilities. • Collaborate with other sales engineers, leaders, and cross-functional technical groups to maintain consistency in approach and application across accounts. • Qualify complex sales opportunities, considering customer technical requirements, competition, decision-making processes, and funding. • Present proposed solution designs and business cases to customers, prospects, and senior management. • Understand and communicate the role of third-party partners and channels in delivering solutions.

• Drive original cybersecurity research initiatives aligned with our strategic objectives • Identify emerging security threats and develop innovative detection and prevention methodologies • Publish research findings through company blog posts, whitepapers, and other outlets • Present research at leading industry conferences and security events • Collaborate with engineering teams to integrate research findings into our product • Mentor junior researchers and foster a culture of exploration and innovation • Establish and maintain relationships with academic and industry research communities • Participate in customer-facing activities

• Own the technical direction for pricing ML. Define what to build and how. Set the roadmap for the pricing engine as a core piece of tem's IP — and be accountable for its performance. • Formulate and solve the pricing problem properly. The mathematical foundation doesn't fully exist yet. Your first job is to define it: a dynamic, real-time system that simultaneously optimises for signing probability, portfolio balance, and margin. Choose the right approach — stochastic programming, reinforcement learning, classical ML, or a hybrid — based on the problem, not familiarity. • Build and ship models end-to-end. Own the modelling and data layer. Write production-grade Python. Architect models with deployment in mind and carry them through to production — you can execute without being blocked by engineering dependencies. • Solve imbalance problems. Develop probabilistic models to optimise risk management and short-term balancing decisions in a highly dynamic environment. • Be the voice of pricing ML across the business. Commercial, product, and engineering teams depend on this engine. They need to understand what it's doing and why. You make that happen — clearly, without losing precision.

• Lead and define statistical analyses to identify cost, utilization, and performance drivers across populations, markets, and payer arrangements. • Partner with data, actuarial, and analytics teams to validate healthcare claims data structures, ensure data is accurately represented in enterprise datasets, and resolve discrepancies affecting downstream reporting and analysis. • Apply economic insights to strengthen impact modeling and quantify the financial and operational implications of clinical and business initiatives. • Develop experimental designs for new program initiatives to ensure programs are set up for impact analysis in advance • Translate complex claims, reimbursement, and utilization data into clear, actionable recommendations for cross-functional stakeholders and senior leadership. • Identify trends, anomalies, and emerging opportunities within claims and performance data, and communicate their implications for value-based care strategy.