• 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.

Role Description This role is responsible for developing predictive models and forecasting frameworks that support marketing performance, customer acquisition, and market targeting, while also contributing to broader internal data science initiatives. The position combines hands-on statistical modeling and machine learning with applied business problem-solving to drive more effective, data-driven decision-making. The role will work closely with BI and analytics partners to ensure alignment between predictive outputs and reporting, helping translate model results (e.g., lead scoring, conversion propensity, and forecasting) into actionable insights. In parallel, this individual will support internal data science and modeling efforts, contributing to the development of proprietary analytics capabilities. The role is expected to initially focus on marketing-related modeling and progressively expand into deeper data science work over time. This position requires a solution-oriented mindset — someone who takes ownership, challenges assumptions, and actively improves processes rather than simply executing tasks. This role is designated at the Analyst level. Key Responsibilities - 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 Qualifications - Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, or related field Requirements - 3 to 7 years of experience in data science, applied modeling, or advanced analytics - Proven experience building and validating predictive models in a business environment - Experience with statistical methods, machine learning techniques, and forecasting approaches - Strong problem-solving skills and ability to translate business problems into analytical solutions - Ability to communicate complex analytical concepts to non-technical stakeholders - Experience with customer acquisition cost modeling and marketing ROI analysis Key Soft Skills - Clear communication: can explain data issues, tradeoffs, and results to both technical and business stakeholders - Collaboration: works effectively across engineering, analytics, and business teams Technical Skills - Strong proficiency in Python and SQL Benefits - USD Base Salary - Enjoy Paid Time Off (PTO) after just 6 months of service - Full-time opportunity - Enjoy the freedom of a completely remote work environment!