Data Scientist

Innoit Consulting
El Lloar, Spain
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Agile Methodology Artificial Intelligence Big Data Information Engineering DevOps Python (Programming Language) Machine Learning Supervised Learning Large Language Models Apache Spark Generative AI Git
+3 more
Pyspark Machine Learning Operations Software Version Control

Job description

We are looking for aData Scientistwith experience in developing and improving Machine Learning models, along with strong knowledge and interest inGenerative AI. You will participate in data and AI projects, working on both existing models and the development of new solutions that deliver real business value.ResponsibilitiesDesign, develop, and optimize Machine Learning models.Analyze and work with large volumes of data and complex datasets.Evaluate, validate, and monitor model performance in production environments.Contribute to the development of solutions based onGenerative AI and LLMs.Work with RAG architectures, embeddings, and AI solutions focused on business use cases.Collaborate with Data Science, Data Engineering, and other technical teams.Apply best practices throughout the model development lifecycle.Communicate insights and results to both technical and business stakeholders.QualificationsExperience as aData Scientistwith a strong understanding of Machine Learning.Experience developing and validating supervised learning models.Knowledge and hands-on experience withGenerative AI, LLMs, and RAG.Strong proficiency inPython.Experience withSpark and PySpark.Knowledge of version control and model management tools such asGit and MLflow.Experience working with large-scale and complex datasets.Familiarity withFeature Stores, Agile methodologies, and DevOpsis a plus.Previous experience in theinsurance industryis highly valued.

Requirements

Experience as a Data Scientist with a strong understanding of Machine Learning. Experience developing and validating supervised learning models. Knowledge and hands-on experience with Generative AI, LLMs, and RAG . Strong proficiency in Python . Experience with Spark and PySpark . Knowledge of version control and model management tools such as Git and MLflow . Experience working with large-scale and complex datasets. Familiarity with Feature Stores, Agile methodologies, and DevOps is a plus. Previous experience in the insurance industry

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