Role Description This role focuses on subscription analytics and initiatives to drive growth. Here, you will partner closely with Product, Business, Data Engineering and Instrumentation teams. The tasks fall broadly into these areas: - Size new opportunities and work with a broad cross-functional team to support roadmap planning, implementation, and launch of new products and features. - Identify key learnings from data and distill findings into recommendations for business owners. - Define, measure and communicate KPIs for overall business and key initiatives. Build and maintain regular reports and provide ad-hoc analysis to support business needs. - Work with engineering to identify data needs for new initiatives and build data pipelines. Partner with the instrumentation team to ensure tracking is in place before launches. Qualifications - 5+ years of experience working and understanding of data structures and pipelines. - 5+ years of experience with demonstrated expertise in programming, developing, and managing SQL, R and/or PySpark. - Bachelor's degree in the preferred fields of Mathematics, Economics, Engineering, Statistics, Business Analytics, Finance, or equivalent quantitative discipline. Preferred Qualifications - Related business understanding with experience in product growth or analytics. - Strong business presentation and storytelling skills. Communication skills to package findings. - Work well within cross-functional teams and manage stakeholders. - Ability to structure and solve problems.

• Atuar de forma colaborativa em equipes multidisciplinares, mantendo comunicação clara e relacionamento harmonioso com diferentes áreas do negócio. • Desenvolver, implementar e manter modelos matemáticos para simulação, otimização e suporte à tomada de decisão em processos da empresa. • Traduzir problemas de negócio em formulações matemáticas (ex.: programação linear, inteira mista, não linear). • Desenvolver soluções computacionais escaláveis, com foco em desempenho, robustez e manutenibilidade. • Escrever código limpo, organizado e bem documentado, seguindo boas práticas de engenharia de software. • Participar do ciclo completo de desenvolvimento das aplicações (análise, modelagem, implementação, testes, validação e evolução). • Trabalhar em conjunto com usuários e stakeholders para entender necessidades, validar resultados e superar expectativas.

Role Description Voyager's Advanced Technologies Group is defining the future of the company and critical space and defense markets. The Material Scientist is a hands-on research role responsible for advancing materials research and computational modeling in support of novel space applications. The role combines scientific rigor with applied machine learning to develop predictive tools and support mission-driven research programs. The scientist works collaboratively across engineering and program teams to drive research from concept through execution. Essential Functions: - Conduct and support materials research across computational and experimental domains. - Develop and apply machine learning and data-driven methods to materials modeling and process optimization. - Assemble, curate, and analyze datasets from simulations, experiments, and scientific literature. - Collaborate with internal engineering teams and external research partners to advance materials knowledge and capabilities. - Translate research findings into actionable guidance for space mission applications. - Write technical reports and presentations; contribute to proposals and design reviews. Qualifications - PhD in Materials Science, Chemical Engineering, Physics, or a related field. - Familiarity with applying machine learning or data-driven methods to scientific or engineering problems. - Experience with computational simulation methods (e.g., MD, DFT). - Strong analytical and problem-solving skills with the ability to work across computational and experimental domains. - Excellent written and verbal communication skills. - Ability to work effectively on multi-disciplinary teams and manage multiple priorities. Requirements - Experience modeling inorganic systems, particularly those relevant to metal alloys and/or semiconductors. - Familiarity with experimental material characterization datasets spanning multiple methods (i.e., XRD, SEM, TEM, EDS, XPS, and spectroscopic techniques). - Curious, detail oriented, and analytical with a proven ability to learn quickly. - Honest, Respectful and Patient. - Ability and willingness to make an impact. - Demonstrated initiative, drive, and interpersonal skills. - Thrives in a dynamic and fast-paced environment. Benefits - Flexible Time Off (FTO), empowering employees to take the time they need to recharge and maintain a healthy work-life balance. - Comprehensive medical, dental, and vision coverage for employees and their families, with a significant portion of premiums covered by the company and many benefits paid at 100% for employees. - Flexible, affordable gym memberships with 12,700+ options nationwide including 24 Hour Fitness, EoS Fitness, Crunch Fitness, Anytime Fitness, Blink Fitness, Chuze Fitness and more! No long-term contracts and FREE on-demand workout videos before you enroll. - 401(k) retirement plan with a 50% company match on contributions up to 8%, supporting long-term financial security. - Company wellness programs that support physical and mental well-being. - Additional voluntary benefits and employee support resources. - The opportunity to work alongside a highly talented team in an innovative, mission-driven environment.

• Develop, validate, and maintain predictive models including lead scoring, conversion propensity, and funnel optimization. • Develop tiering models to prioritize leads by conversion probability. • Build forecasting frameworks for lead volume, conversion rates, and pipeline or revenue projections. • Build channel performance models to optimize budget allocation across paid search, email, ISO partners, etc. • Monitor model performance and iterate to improve accuracy and business impact. • Develop models to evaluate and prioritize markets based on expected performance and ROI. • Analyze geographic, industry, and segment-level trends to identify growth opportunities. • Support data-driven recommendations on market targeting and resource allocation. • Support campaigns/future product launches by forecasting lead volume, conversion rates, and CAC by channel. • Design and analyze experiments (A/B testing, cohort analysis) and evaluate incremental impact. • Apply statistical and machine learning techniques to solve marketing and business problems. • Conduct deep-dive analyses to support strategic and operational decisions. • Contribute to internal data science and modeling initiatives, including proprietary or internal IP work. • Collaborate with Data Engineering to structure and prepare datasets for modeling. • Partner with BI and analytics teams to ensure model outputs are integrated into reporting and usable by stakeholders.