Role Description Lightly AG is looking for analytical and driven Geopolitical and Event Forecasting Professionals to help evaluate AI-generated predictions about real-world events. The estimated project scope is approximately 15 hours/week. - Evaluate AI-generated event forecasts by assessing the accuracy and quality of predictions covering elections, central bank decisions, policy announcements, and technology/regulatory events using a provided rubric. - Project expected to begin early July. Qualifications - At least 2-3 years of recent experience in political analysis, macroeconomics, geopolitical risk, or policy research. - Experience producing or evaluating probabilistic forecasts - election modelling, policy impact assessments, or macro scenario analysis. - Familiarity with prediction markets (Polymarket, Metaculus) or superforecasting methodologies. - Fluency in English (requirement). - Strong analytical and quantitative skills. - Ability to communicate clearly and precisely. Benefits - Work directly with a YC-backed team on cutting-edge AI evaluation projects. - Competitive compensation tailored to experience and scope of work. Company Description Lightly AG is an ETH and HSG spin-off pioneering in machine learning and computer vision. We are backed by Y Combinator and top-tier investors, and our technology is used by global leaders in autonomous driving, medical imaging, and visual inspection.

Role Description The STS AI & Data Engineering Apprenticeship is a year-long, structured program designed to develop the next generation of AI, data, cloud, and automation professionals through hands-on projects, mentorship, and real-world experience. STS takes an individualized approach — each apprentice receives a customized development roadmap built around their career goals, current skills, and alignment with STS business needs. The program spans three progressive phases: - Foundational skills development - Applied learning alongside experienced STS mentors - Career transition period that supports a smooth entry into a full-time professional consulting role By program completion, apprentices will have the technical, professional, and consulting skills to contribute meaningfully to AI, data, cloud, and digital transformation initiatives at STS and for our federal and commercial clients. The AI & Data Engineering Apprentice at STS will: - Complete structured learning plans covering AI, machine learning, data engineering, cloud platforms, and software development fundamentals. - Participate in hands-on labs, guided exercises, and practical projects to build a strong technical foundation. - Pursue industry certifications in relevant technology areas as outlined in their individualized development roadmap. - Engage in pair programming, collaborative development, and AI solution-building projects alongside experienced STS mentors. - Contribute to internal innovation and automation projects, data engineering initiatives, and cloud modernization efforts. - Develop proficiency with leading AI tools and platforms, including generative AI frameworks, LLMs, cloud services, and data analytics platforms. - Apply responsible AI, data governance, and security best practices throughout all work. - Participate in professional development coaching, career planning, and client engagement preparation activities. - Transition into a full-time STS consulting role upon successful completion of the program, with continued mentorship during the first 90 days of employment. Qualifications - High School Diploma or GED equivalent - No prior professional experience required; this is an entry-level program - Demonstrated interest in technology, data, or AI through coursework, self-study, personal projects, or extracurricular activities - Strong analytical thinking and problem-solving skills - Effective written and verbal communication skills - Ability to work independently and collaboratively in a fast-paced, project-driven environment - Commitment to continuous learning and professional growth throughout the duration of the program Requirements - Bachelor's Degree in Computer Science, Information Technology, Data Science, or related field (in progress or completed) - Foundational exposure to Python, SQL, or cloud platforms (AWS or Azure) - Prior coursework or training in data analysis, software development, or artificial intelligence - Experience with collaboration tools such as GitHub or Agile project management platforms Benefits - Flexibility to help team members thrive personally and professionally - Special incentives for team members living in qualified HUBZones

• Support research and studies related to Artificial Intelligence • Test and explore AI tools applied to software development and software quality • Assist in creating prompts, automated workflows and small prototypes • Support initiatives to automate tasks using AI • Participate in documenting processes, tests and learnings • Collaborate with Software Quality, Automation and Development teams • Contribute ideas for continuous improvement of processes and products • Participate in project meetings, training sessions and activities.

• Define and own the AI roadmap, starting with go-to-market and expanding across the business, from use-case discovery and prioritisation through to delivery, adoption and measurement. • Identify where AI, automation and workflow redesign can remove friction, in go-to-market first and then the wider business. • Act as the connective tissue between business stakeholders and technical teams, translating operational challenges into concrete, prioritised delivery work. • Build a clear intake, prioritisation and delivery model for AI use cases, ensuring the team focuses on high-impact problems rather than isolated experiments. • Evaluate build vs. buy decisions across AI tooling, workflow automation, business systems and internal productivity tools. • Champion practical, responsible AI adoption across the company, ensuring what gets built is useful, trusted and embedded into how people work. • Partner with Legal, Security, IT, Data Warehouse and Analytics teams to ensure AI adoption is scalable, compliant and aligned with internal governance. • Help teams move from AI experimentation to repeatable workflows that improve productivity, quality, accuracy and decision-making. • Lead and develop your Engineering Manager, who owns day-to-day technical execution for the technical delivery team. • Set technical direction and priorities alongside the EM by challenging scoping, reviewing tradeoffs, and removing blockers. • Provide enough technical fluency to challenge assumptions, evaluate solutions, and ensure the right problems are being solved in the right way. • Work closely with Data Warehouse and Analytics teams to ensure AI workflows are grounded in reliable data and aligned with existing data architecture. • Foster a culture of experimentation, pragmatic delivery, continuous improvement and measurable business impact. • Ensure AI and automation initiatives are delivered with appropriate documentation, ownership, adoption plans and feedback loops. • Own Revenue Operations: the systems and data behind the revenue engine (CRM, pipeline, lead routing and forecasting). • Make RevOps one of the first proving grounds for AI: improve accuracy, speed and rep productivity, and build it. • Drive operational change that sticks, ensuring teams do not just receive new tools but adopt better ways of working. • Build trust with senior stakeholders by clearly communicating priorities, trade-offs, risks and expected outcomes. • Create practical enablement, guidance and feedback mechanisms to support AI adoption across different functions. • Measure adoption and impact, using feedback and business outcomes to refine the AI Operations roadmap. • Help the business distinguish between genuine AI opportunities and low-value experimentation or hype.