Job Opportunity: Data Scientist / Machine Learning Engineer
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Position Overview
We are seeking a talented Lead Data Scientist/ML Engineer to join an embedded team. In this role, you will be crucial in developing and implementing machine learning solutions for several projects. Your expertise will be essential in driving the success of the company initiatives.
About the Customer
The client is the largest Google digital consulting agency in Europe, operating only in the Google cloud.
Requirements
Background in the Data Science/Machine Learning area (4+ years)
Proven experience starting new Machine Learning projects from scratch: from problem analysis and data collection to PoC and deployment to production
Expertise with Generative AI (RAG applications, Prompt Engineering)
Confidence in Python, Pandas, Scikit-learn, Matplotlib, SQL, etc.
Competency in Machine Learning algorithms, their limitations, and use cases
Knowledge of how to set up MLOps
A sharp-minded person who can dive into the business domain and emerge with ideas on how to use data to make the business more effective
A creative person who can convert the data into a story with plots and insights
Strong communicator who can speak to a client face-to-face, understand business needs, and explain the solution in an easily digestible way
Nice to Have
MS or BS in computer science or related field
Expertise in ML/DL frameworks (PyTorch, TensorFlow, etc.)
Familiarity with micro-service architecture, task queues (e.g., Celery), cloud (e.g., AWS or Azure), Docker, OS and networking basics, and database systems (e.g., Postgres, Kaggle or GitHub) account with projects that demonstrate skill level
English level Upper-Intermediate
Responsibilities
Lead an AI development team
Understand business objectives and models that help achieve them
Propose and realize new ideas to benefit our customers and the company
Fully cover (develop, maintain, and monitor) the entire lifecycle of created models
Propose new research, improvements, and best practices
Share knowledge, ideas, and new approaches with team members
Stay up-to-date with the latest findings in applied data science
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