TRIONIKA

Infopulse, Part of TietoEvry Create, is inviting a talented professional to join our growing team as a 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.
  • Proficiency 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.