Senior Data Scientist - AdTech (6-month Contract)

Proximity Works · Remoto · Remote

Recebendo candidaturas · conferida em 27/10

Ficha da vaga

Modelo
Remoto
Onde aceita
Não informado
Senioridade
Sênior
Salário
Salário não divulgado

Fonte: Workable · Ver vaga original →

  • python
  • sql
  • analise dados
  • cloud basico
  • resolucao problemas
  • foco resultados
  • autogestao
  • colaboracao
  • estatistica basica

Organizei a descrição em seções com IA. O texto completo da vaga está logo abaixo.

Sobre a vaga

Proximity Works is seeking a Senior Data Scientist with 5+ years of experience for a 6-month contract to build, deploy, and optimize machine learning models at scale using Python, SQL, Spark, and AWS.

O que você vai fazer

  • Design, build, and deploy scalable machine learning models into production systems.
  • Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
  • Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
  • Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
  • Collaborate with engineering teams to integrate models into cloud-based applications on AWS.

O que pedem

  • Minimum of 5 years of experience.

Descrição completa da vaga

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

Design, build, and deploy scalable machine learning models into production systems. Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch). Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training. Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration. Collaborate with engineering teams to integrate models into cloud-based applications on AWS. Optimize query performance, storage usage, and data pipelines for efficiency. Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment. Drive initiatives independently with high ownership and accountability. Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

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