Ofertes d'ocupació a Keyrus

• Flexibilitat horàriaSi
• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada2 de març

Python Agile TSQL Azure Cloud Coumputing AWS Machine Learning Power BI

THE PLACE TO BE

Empowered by our motto, "making data matter," Keyrus stands at the forefront of global consultancy in Data & Analytics, AI &Machine Learning, and Digital Transformation.

With a presence in 27 countries across 4 continents, we're on a mission to help our clients to improve their performance leveraging technological and functional expertise in data and analytics.

We are data experts, guiding our clients through their data journey regardless of their level of maturity in analytics. As an end-to-end partner, we address varied challenges that our clients face, from Advanced Analytics, Cloud, Data Governance, Visualisation to Enterprise Performance Management, from advisory to delivery.

With more than 3200 employees in all corners of the world, we help our clients on a global level with extensive knowledge, a start-up mindset, and a powerful international network.

Job Description

• Identify, scope, and implement data preparation actions to maximize AI model success.
• Perform data profiling, cleansing, standardization, deduplication, matching, enrichment, and completion.
• Analyze diagnostic results from the Data Cube to identify and address key data challenges.
• Prioritize data preparation tasks to support pilot projects, utilizing a micro-actions approach for quick, impactful results.
• Design and implement a data transformation architecture to support AI and ML initiatives.
• Develop, train, evaluate, fine-tune, and optimize AI/ML models.
• Apply best practices in feature engineering, hyperparameter tuning, and model performance enhancement.
• Ensure AI models align with business needs and technical feasibility.
• Work in an agile environment, iterating through sprints to refine models and drive business value.
• Contribute to AI adoption through a structured methodology focused on cost-efficiency and risk reduction.
• Evaluate Technical Complexity vs. Business Impact vs. Execution Cost to determine feasibility.
• Implement AI-driven solutions that enhance data preparation and business use cases.
• Communicate AI-driven insights effectively to stakeholders.
  
  

• Bachelor's or Master’s degree in Computer Science, Data Science, AI, or a related field.
• Strong experience in Machine Learning, Generative AI, and AI Model Development.
• Proficiency in data processing and analytics tools such as Power BI, Alteryx, Python, and SQL.
• Expertise in data preparation techniques, including cleansing, transformation, and enrichment.
• Familiarity with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Ability to identify and address data-related challenges.
• Strong understanding of data architecture and AI/ML model optimization.
• Strong communication skills to translate technical findings into business insights.Agile mindset with experience working in iterative development cycles.
• Fluent in English
• Fluent in Spanish
  
  

• Experience working with AI-driven data preparation frameworks.
• Knowledge of cloud-based AI solutions (AWS, Azure, Google Cloud).