• Desenvolvimento de Modelos Preditivos: Desenvolver modelos de propensão a default utilizando técnicas de ML tradicional (classificação binária, modelos ensemble como Random Forest, Gradient Boosting e equivalentes), com foco em precisão, recall e estabilidade em produção. • Seleção e Engenharia de Features: Conduzir análise exploratória de dados (EDA), identificar e selecionar variáveis relevantes a partir de dados contratuais estruturados e, progressivamente, incorporar variáveis externas (clima, safra, cenário macroeconômico, dados de recuperação judicial e fontes de notícias). • Experimentação no Databricks: Desenvolver e versionar experimentos de modelagem utilizando Databricks e MLflow, garantindo rastreabilidade de runs, parâmetros, métricas e artefatos de modelos ao longo dos ciclos iterativos. • Validação e Avaliação de Modelos: Projetar e executar estratégias robustas de validação (cross-validation, backtesting temporal, análise de estabilidade de score) garantindo que os modelos performem de forma confiável em janelas de projeção crescentes (3, 6 e 12 meses). • Ciclos Iterativos de Melhoria: Participar ativamente dos ciclos iterativos de refinamento do modelo — a cada sprint, incorporar novas variáveis, reavaliar performance e documentar aprendizados na Base de Conhecimento do programa. • Colaboração com Engenharia de Dados: Trabalhar em estreita parceria com os Data Engineers para garantir que os pipelines de dados alimentem corretamente os modelos, e que as saídas dos modelos (scores, projeções, alertas) sejam disponibilizadas nas camadas corretas da plataforma. • Comunicação de Resultados: Traduzir resultados técnicos dos modelos para linguagem de negócio, apoiando o Data Strategist na comunicação com stakeholders do cliente (superintendências, crédito, liderança). • Documentação Técnica: Documentar metodologias, decisões de modelagem e resultados em formatos estruturados que alimentem a Base de Conhecimento e possam ser consumidos por agentes de IA em fases subsequentes. • Monitoramento em Produção: Acompanhar a performance dos modelos em produção, identificar desvios de distribuição (data drift, concept drift) e propor ações corretivas ou re-treinamentos.

• Build and maintain the core BI dashboard suite that gives Sales and Marketing self-serve, real-time visibility into pipeline health, funnel conversion, segment-level coverage, campaign contribution, rep attainment, and loss analysis. • Own the GTM data dictionary — metric definitions, filter logic, and calculation rules — and maintain it as the authoritative source of truth across Marketing, Sales, and Finance. • Own the analytical layer of the GTM forecast process: historical conversion rates, pipeline coverage analysis, stage-weighted modeling, and forecast variance diagnosis. • Lead annual bookings planning analysis — historical win rates, segment-level capacity modeling, coverage assessments, and quota calibration inputs — and partner with Strategic Finance on revenue forecasting and GTM investment analysis. • Build scenario models for pricing, segmentation, and GTM structure decisions as needed by RevOps and Sales leadership. • Track campaign performance relative to pipeline contribution goals by segment; surface what's generating pipeline, what isn't, and where investment is misallocated. • Partner with Analytics Engineering to ensure GTM data from Salesforce, Marketo, and adjacent systems is correctly modeled in the data warehouse — flag gaps, validate logic, and escalate data quality issues. • Lead ad-hoc analytical projects supporting key company initiatives: segmentation analysis, market sizing, cohort analysis, win/loss diagnostics, and product-GTM intersection analysis.

• Develop, implement, and maintain machine learning and statistical models to support mission and program objectives • Analyze large structured and unstructured datasets to identify trends, anomalies, and actionable insights • Apply predictive analytics, classification, and regression techniques to real-world operational problems • Build and optimize data pipelines, ETL processes, and feature engineering workflows • Develop data visualization dashboards and reporting tools to communicate findings to technical and non-technical stakeholders • Work with cloud or on-premise environments to deploy scalable data solutions • Support test, evaluation, and analysis efforts for aviation, weapons systems, or mission systems programs • Provide data-driven recommendations to engineering teams, program managers, and government stakeholders • Interface with cross-functional teams including systems engineers, software developers, and analysts • Collaborate across IPTs to translate mission requirements into analytical solutions • Document methodologies, models, and results in accordance with DoD and program standards • Present findings to stakeholders in a clear and concise manner

Role Description Saalex is seeking a highly motivated Data Scientist to support mission-critical programs at China Lake. This role will focus on developing and deploying advanced analytical models, supporting test and evaluation efforts, and transforming complex datasets into actionable insights for engineering, operational, and leadership teams. Essential Functions - Data Analysis & Modeling - Develop, implement, and maintain machine learning and statistical models to support mission and program objectives. - Analyze large structured and unstructured datasets to identify trends, anomalies, and actionable insights. - Apply predictive analytics, classification, and regression techniques to real-world operational problems. - Technical Development - Build and optimize data pipelines, ETL processes, and feature engineering workflows. - Develop data visualization dashboards and reporting tools to communicate findings to technical and non-technical stakeholders. - Work with cloud or on-premise environments to deploy scalable data solutions. - Mission & Program Support - Support test, evaluation, and analysis efforts for aviation, weapons systems, or mission systems programs. - Provide data-driven recommendations to engineering teams, program managers, and government stakeholders. - Interface with cross-functional teams including systems engineers, software developers, and analysts. - Collaboration & Documentation - Collaborate across IPTs to translate mission requirements into analytical solutions. - Document methodologies, models, and results in accordance with DoD and program standards. - Present findings to stakeholders in a clear and concise manner. Qualifications - Experience supporting DoD, aerospace, or government programs strongly preferred. Requirements - Technical Skills: - Advanced proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). - Strong experience with SQL and relational databases. - Experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn). - Solid understanding of machine learning techniques (classification, regression, clustering, NLP, etc.). - Data Engineering & Systems: - Experience building data pipelines and ETL processes. - Familiarity with cloud platforms (AWS, Azure, or similar) or on-prem DoD environments. - Understanding of data architecture and large-scale data processing. - Analytical Skills: - Strong statistical analysis and modeling experience. - Ability to translate complex data into actionable insights. - Demonstrated problem-solving skills in ambiguous or evolving environments. - Collaboration & Communication: - Ability to work effectively within cross-functional teams and IPT structures. - Strong verbal and written communication skills. - Experience briefing technical and non-technical stakeholders. Education - Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related technical field, or equivalent practical experience required. Security Clearance - Active Secret Clearance required. Requirements to obtain a clearance include US Citizenship, security investigation, etc. Benefits - Health Care Plan (Medical, Dental & Vision). - Retirement Plan (401k, IRA). - Life Insurance (Basic, Voluntary & AD&D). - Paid Time Off (Vacation, Sick & Public Holidays). - Short Term & Long Term Disability. - Training & Development. - Wellness Resources. - Stock Option Plan.