Senior Engineer, Data Science – Machine Learning Operations

🕒 Maio 21

🎸 Tennessee – Remoto

🎸 Tennessee – Remote

💵 $165.000 - $200.000 / ano

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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Tivity Health

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 1981

⚕️ Seguro de Saúde

🧘 Bem-estar

💰 Post-IPO Equity em 2013-10

Healthcare Insurance • Wellness • Fitness

Tivity Health é uma empresa dedicada a melhorar os resultados de saúde e reduzir os custos de assistência médica por meio de programas inovadores de fitness e bem-estar. Eles capacitam indivíduos, especialmente a população idosa, a se engajar em atividades físicas e melhorar sua saúde geral por meio de marcas como SilverSneakers, que promove um estilo de vida ativo para idosos, e Prime Fitness, que proporciona acesso a instalações de fitness em todo o país. A Tivity Health enfatiza uma abordagem centrada no membro e orientada por dados para facilitar comportamentos saudáveis em várias fases da vida, tornando a saúde e o bem-estar acessíveis a todos.

Descrição

• Partner directly with business stakeholders to identify opportunities where data and machine learning can improve decisions, efficiency, or outcomes • Design experiments and hypotheses that can be validated quickly using available data and pragmatic modeling approaches • Own models end-to-end—from data preparation and feature engineering through deployment, monitoring, and iteration based on real-world results • Deploy ML models into production using AWS-native tooling and integrate them into operational workflows and downstream systems • Implement ML training and inference pipelines on Amazon SageMaker, including pipelines, endpoints, model registry, and monitoring • Monitor model performance (accuracy, drift, stability, business KPIs) and iterate based on real-world impact • Build and operate data ingestion and transformation pipelines across batch and event-driven workloads using AWS Glue, zero‑ETL integrations, Step Functions, EventBridge, and related services • Collaborate closely with IT, Security, and Platform Engineering teams to align with enterprise security, compliance, and operational standards • Use infrastructure as code (Terraform, CDK, or CloudFormation) to create repeatable, scalable environments • Own and operate S3-based data lake infrastructure, including Iceberg table formats, AWS Glue Data Catalog, and AWS Lake Formation • Implement and enforce data zone architecture (e.g., raw, curated, and consumption zones) to support governed data access and lifecycle management • Define and apply data access controls using Lake Formation permissions and IAM-aligned policies • Establish and maintain data governance practices, including schema management, schema evolution, and lineage tracking • Ensure data assets are discoverable, auditable, and secure through cataloging, metadata management, and access controls • Build end-to-end observability using CloudWatch, Datadog, pipeline SLAs, data quality checks, and model drift detection • Establish operational runbooks and support procedures for governed data and ML platforms • Apply cost-aware design when selecting data processing, training, and inference approaches • Optimize Glue, SageMaker, and storage usage to deliver value efficiently at scale • Continuously improve platform reliability, scalability, and cost efficiency as data and ML workloads grow

🎯 Requisitos

• 5+ years in a professional data science role • 5 years of experience with machine learning pipelines, preferably in an AWS environment • Applied problem solver motivated by business outcomes and action • Strong business partner able to translate questions into testable hypotheses and executable solutions • Hands-on applied ML experience delivering models into production AWS environments • Proven experience operating governed data lakes and ML platforms at scale • Builder–operator mindset with strong CI/CD, observability, and incident response skills • Pragmatic practitioner who values reliability, adoption, governance, and impact over unnecessary complexity

🏖️ Benefícios

• competitive salary • company bonus potential • medical, dental, vision • 401k with match • generous paid time off • free gym membership to over 13,000 fitness locations in the US • other great benefits