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Senior Data Scientist (m/f/d/v) in Infopulse

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Infopulse

Infopulse

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3 вересня 2024 Senior Data Scientist (m/f/d/v) Київ, Львів, Одеса, Вінниця, Івано-Франківськ, Житомир, Софія (Болгарія), Варна (Болгарія) Infopulse, Part of TietoEvry Create, is inviting a talented professional to join our growing team as  Senior Data Scientist . Areas of Responsibility Solution Design and Architecture Design and architect end-to-end data science solutions that align with business objectives and technical requirements. Develop scalable and maintainable data science

3 вересня 2024

Senior Data Scientist (m/f/d/v)

Київ, Львів, Одеса, Вінниця, Івано-Франківськ, Житомир, Софія (Болгарія), Варна (Болгарія)

Infopulse, Part of TietoEvry Create, is inviting a talented professional to join our growing team as  Senior Data Scientist .

Areas of Responsibility

Solution Design and Architecture

  • Design and architect end-to-end data science solutions that align with business objectives and technical requirements.
  • Develop scalable and maintainable data science workflows, including data ingestion, preprocessing, modeling, and deployment.
  • Ensure the integration of data science solutions with existing systems and platforms.

Solution Implementation and Deployment

  • Oversee and participate in implementing data science solutions, including developing and deploying machine learning models.
  • Ensure solutions are robust, scalable, and perform well in production environments.
  • Conduct code reviews and ensure adherence to coding standards and best practices.

Performance Optimization and Troubleshooting

  • Optimize the performance of data science solutions, including model accuracy, computational efficiency, and resource utilization. Improve efficiency by creating repeatable and reusable modules
  • Troubleshoot and resolve technical issues related to data science solutions.

Technical Leadership

  • Provide technical leadership and guidance to data scientists, data engineers, and other stakeholders.
  • Stay updated with the latest advancements in data science, machine learning, and AI technologies, and apply them to improve solution designs.

Data Strategy and Governance

  • Define data strategy and governance frameworks to ensure data quality, security, and compliance.
  • Establish best practices for data management, including data acquisition, storage, and processing.

Collaboration and Communication

  • Work closely with business stakeholders to understand their needs and translate them into technical requirements.
  • Communicate complex technical concepts to non-technical stakeholders clearly and concisely.
  • Foster a collaborative environment to facilitate knowledge sharing and innovation.

Qualifications

  • 5+ years of experience in the field.
  • Strong programming skills in languages such as Python, R, or Scala.
  • Machine Learning Frameworks and Libraries.

    • Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Generative AI (GenAI).
    • Experience with Generative AI models (e.g., GPT, BERT, DALL-E) and frameworks (e.g., Hugging Face Transformers, OpenAI GPT-3).
    • Knowledge of fine-tuning GenAI models for specific tasks and industries.
    • Ability to design and implement GenAI solutions for various applications such as text generation, image generation, and conversational AI.
    • Familiarity with techniques for training and deploying GenAI models.
    • Experience in leveraging GenAI for tasks such as automated content creation and data augmentation.
  • MLOps.
    • Proficiency in MLOps practices, including model deployment, monitoring, and continuous integration/continuous deployment (CI/CD) for machine learning models.
    • Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, TFX).
  • Data Manipulation and Analysis.
    • Proficiency in data manipulation and analysis using SQL and data processing tools (e.g., Apache Spark, Hadoop).
  • Cloud Platforms.
    • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data science and machine learning services.
    • Understanding of cloud infrastructure and services for scalable AI deployments.
  • Containerization and Orchestration.
    • PProficiency in containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for deploying and managing data science solutions.
  • Big Data Technologies.
    • Experience with big data technologies (e.g., Apache Kafka, Apache Flink) for handling and processing large datasets.

Will be an advantage

  • A degree in Data Science and/or Mathematics.

Personal skills

  • At least an Upper Intermediate level of English.

Without experience
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