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Data Scientist (ML)

Terminal.com

Terminal.com

Software Engineering, Data Science
Spain
Posted on Sep 4, 2023
About ModuleQ
Headquartered in Cupertino, California, ModuleQ connects the dots in work data by tapping into the largest databases, the latest news, and internal content. With consent, ModuleQs People-Facing AI creates a network of intelligence in clients existing workspace to identify priorities. ModuleQ uses proprietary algorithms to search public and internal information as well as business intelligence from partners.
What you'll do
  • Identify and source relevant structured and unstructured data from various internal and external sources.
  • Collect, preprocess, and transform data into usable formats, ensuring accuracy, completeness, and quality.
  • Build and curate datasets by labeling and annotating data for supervised and unsupervised learning.
  • Develop and implement state-of-the-art algorithms and models that underpin AI features and capabilities.
  • Perform thorough data and error analysis to continuously refine and enhance AI models' performance.
  • Cleanse and validate data, ensuring consistency and uniformity to optimize model performance.
  • Analyze data to identify trends, patterns, and insights that drive informed decision-making.
  • Conduct experimental analyses to derive meaningful insights, contributing to product innovation.
  • Collaborate closely with engineering and product teams to comprehend requirements and translate them into effective AI features.
  • Facilitate the seamless transition of AI solutions from development to production environments.
  • Communicate findings, recommendations, and insights to technical and non-technical stakeholders.
  • Collaborate on interdisciplinary projects, fostering a culture of cross-functional teamwork.
What you bring
  • Master's Degree in Computer Science, Algorithms, or a relevant field
  • Excellent communication skills
  • The candidate should have experience with modern machine learning and data science toolkits such as PyTorch/Tensorflow, Pandas, NumPy, Scikit-learn, Jupyter/Python.
  • Experience with training transformers, MLOps and tools such as SpaCy and Azure ML is a plus, as is experience with C#