Senior Data Science Leader

hace 18 horas

Madrid, Madrid, España Aveva Denmark A tiempo completo
Job Title: Lead Data Scientist

Aveva Denmark is a global leader in industrial software, and we're seeking a talented Lead Data Scientist to join our team. As a key member of our organization, you will play a pivotal role in solving complex business problems and discovering business insights using quantitative disciplines and visualization techniques.

Key Responsibilities:
  • Guide and inspire the organization about the business potential and strategy of artificial intelligence (AI) and data science.
  • Identify AI business opportunities and collaborate across the business to understand IT and business constraints.
  • Prioritize, scope, and manage data science projects and the corresponding key performance indicators (KPIs) for success.
  • Apply various machine learning (ML) and advanced analytics techniques to perform diverse classification or prediction tasks.
  • Integrate domain knowledge into the ML solution, such as understanding financial risk, customer journey, quality prediction, sales, and marketing.
  • Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options.
  • Train and coach peers on specialist data science topics and promote collaboration with other analytics teams within the organization.
Requirements:
  • At least 5 years of experience in a Lead Data Scientist role, ideally managing a team of 3 data scientists.
  • Proficiency in Python, R, SQL, and other data science coding languages.
  • Demonstrable experience with Databricks platform, Azure ML, or other data science platforms.
  • Experience with large language models (LLM) is highly desirable, particularly Azure OpenAI, Databricks DBQ, etc.
  • Strong knowledge and experience in statistical and data mining techniques, such as generalized linear models (GLM), random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural networks (CNN), and recurrent neural networks (RNN).
  • Expertise in solving problems related to vision, text analytics, credit scoring, failure prediction, and propensity to buy.
  • Ability to work in diverse, cross-functional teams in a dynamic business environment.

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