Senior Data Scientist

🕒 Junho 11

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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Quantiphi

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2013

🤖 Inteligência Artificial

🏢 Corporativo

📚 Educação

💰 Series A em 2019-12

Artificial Intelligence • Enterprise • Education

A Quantiphi é uma empresa líder em engenharia digital orientada por IA que utiliza uma década de experiência no setor para capacitar negócios por meio de soluções de IA escaláveis, seguras e adaptáveis. Ao integrar tecnologia de ponta com aplicações do mundo real, a Quantiphi transforma organizações em vários setores, incluindo saúde, finanças, educação e varejo. Seus serviços abrangem aplicações de IA, análises de dados, modernização de infraestrutura em nuvem e implementações personalizadas de IA. A Quantiphi faz parcerias com gigantes da tecnologia como AWS, Google Cloud, NVIDIA e outros para impulsionar a adoção de IA e oferecer oportunidades transformacionais para empresas.

Descrição

• Lead end-to-end data science initiatives for predictive analytics use cases such as demand forecasting, churn prediction, and risk modeling. • Translate business requirements into ML problem statements and define appropriate modeling approaches. • Design, build, and deploy machine learning models using traditional ML techniques (regression, classification, clustering, time series). • Drive feature engineering, data preparation, and exploratory data analysis to improve model performance. • Develop and manage scalable ML pipelines from data ingestion to model deployment. • Deploy and manage models on AWS using services such as SageMaker. • Ensure model performance through validation, monitoring, and periodic retraining. • Collaborate with data engineering and MLOps teams to productionize ML solutions. • Apply best practices for model governance, explainability, and responsible AI. • Mentor junior data scientists and provide technical leadership while remaining hands-on. • Communicate insights, model outputs, and recommendations effectively to business stakeholders.

🎯 Requisitos

• 8+ years of relevant hands-on technical experience implementing, and developing cloud solutions on AWS. • Strong experience leading predictive analytics initiatives using traditional ML techniques including regression, classification, clustering, and time series forecasting. • Hands-on experience with time series forecasting models including SARIMA, Prophet, and other ML-based forecasting approaches. • Proficiency in Python with experience in libraries such as scikit-learn, XGBoost, Pandas, NumPy. • Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. • Proven ability to translate complex business problems into scalable ML solutions, driving feature engineering strategies and end-to-end model development. • Hands-on experience on AWS Machine Learning services. • Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs. • Experience leading model deployment on AWS SageMaker with a strong focus on performance optimization, model governance, and measurable business impact. • Implement and manage MLOps based model lifecycle and best practices for ML architecture in production environments. • Experience with at least one of the workflow orchestration tools, Airflow, StepFunctions, SageMaker Pipelines, Kubeflow etc. • Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc. • Experience in building model monitoring and explainability workflows in production environments. • Experience defining and driving model governance frameworks and performance monitoring strategies in production environments. • Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions. • Experience with Generative AI development. • Experience working on Infrastructure as Code (IaC) and CI/CD pipelines.

🏖️ Benefícios

• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale. • Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges. • Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents. • Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.