Atuar na área de Compliance Riscos Financeiros, projetando, desenvolvendo, validando e implantando modelos estatísticos, algoritmos de Machine Learning e soluções baseadas em Inteligência Artificial para apoiar processos de Compliance e Gestão de Riscos Não Financeiros.
Responsibilities
Projetar, desenvolver, validar e implantar modelos estatísticos, algoritmos de Machine Learning e soluções baseadas em Inteligência Artificial para apoiar processos de Compliance e Gestão de Riscos Não Financeiros
Desenvolver indicadores preditivos e mecanismos de monitoramento contínuo, contribuindo para o fortalecimento da abordagem baseada em risco
Evoluir e aprimorar modelos analíticos existentes, garantindo aderência às necessidades do negócio, às melhores práticas de mercado e aos requisitos regulatórios
Apoiar revisões técnicas de modelos, códigos-fonte, pipelines e arquiteturas analíticas, assegurando qualidade e robustez das soluções
Disseminar boas práticas relacionadas à modelagem estatística, Machine Learning, MLOps, Inteligência Artificial e governança de modelos
Requirements
Formação superior em Estatística, Matemática, Ciência de Dados, Engenharia, Economia, Física, Computação ou áreas correlatas
Lead strategy, architecture, delivery, and operation of LPL's core data platforms, modernize books‑and‑records capabilities, and build an AI‑native organization focused on trusted, real‑time, agent‑ready data.
Compensation
Pay Range: $207,648.00 - $346,080.00
Responsibilities
Own the strategy, architecture, and delivery of real‑time, event‑driven books‑and‑records platforms
Lead AI‑driven ingestion, normalization, entity resolution, anomaly detection, and quality controls
Modernize security master and pricing capabilities
Build and govern semantic data products
Expose core data through secure, governed APIs and Model Context Protocol services
Strong hands-on expertise in Python and end-to-end AI/ML model development, including data preparation, feature engineering, training, evaluation, and production integration.
Compensation
Rate: $60/hr
Responsibilities
Translate business requirements into scalable AI/ML solutions
Collaborate with architects, data engineers, application teams, QA, and business stakeholder
Use analytical skills and data science knowledge to create real-world impact by developing algorithms and systems to turn disparate data points into objective answers for clients.
Compensation
The projected compensation range for this position is $61,900.00 to $141,000.00 (annualized USD).
Responsibilities
Develop algorithms and systems to turn complex data sets into useful information to solve global challenges.
Work closely with clients to understand their questions and needs and dig into data-rich environments.
Develop predictive data models and perform quantitative analyses.
Build robust and scalable data engineering pipelines with varied datasets and data types.
Requirements
Bachelor’s degree (scheduled to obtain by Winter 2026)
Lead an innovative research program developing, translating, benchmarking, and validating AI methods to improve the practice of radiology by characterizing, reconstructing, enhancing, segmenting, classifying and/or interpreting medical images, and linking them to other imaging (e.g., pathology, ophthalmology, -omics), clinical, biological, wearables and/or -omics data.
Compensation
Assistant Professor: $234,000 - $263,000
Associate Professor: $281,000 - $308,000
Professor: $334,000 - $409,000
The expected base pay range for this position (with diagnostic radiology clinical role) is:
Assistant Professor: $453,000 - $471,000
Associate Professor: $486,000 - $504,000
Professor: $524,000 - $551,000
Responsibilities
Developing, translating, benchmarking, and validating AI methods to improve the practice of radiology
Characterizing, reconstructing, enhancing, segmenting, classifying and/or interpreting medical images
Linking medical images to clinical, biological, wearables and/or -omics data
Requirements
PhD in computer science, engineering, physics, biomedical informatics, data science, imaging science, or another related field
Design and develop large-scale data pipelines and ETL/ELT solutions on Azure Databricks, LakeBase and Spark, enabling machine learning algorithms, business intelligence dashboards, and data products.
Responsibilities
Design and develop ETL/ELT solutions on Azure Databricks, LakeBase and Spark
Develop, implement, and deploy large scale data pipelines empowering machine learning algorithms, insights generation, business intelligence dashboards, reporting and new data products
Design, build, optimize, and manage modern large-scale data pipelines ETL/ELT processing to support data integration for analytics, machine learning features and predictive modelling
Consume data from a variety of sources and formats
Write advanced / complex SQL with performance tuning and optimization
Requirements
Bachelor's degree in Computer Science, Engineering, Mathematics or related discipline
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