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Microsoft
Applied Scientist
Posted on Nov. 19, 2024
- Dublin, Ireland
- 0 - 0 USD (yearly)
- Full Time
At Microsoft 365 Customer Success Engineering, we are dedicated to creating experiences that help our customers maximize the value of our products. We are seeking motivated and enthusiastic AI practitioners eager to develop innovative solutions that tackle real-world challenges and delight our customers, ultimately driving their success.
Successful candidates will join a newly formed team of Applied Scientists on an exciting mission. We value intellectual curiosity, critical thinking, and expertise in artificial intelligence. A strong aptitude for learning and applying AI solutions is essential. Team members will implement these solutions in a commercial environment, leveraging the Azure Cloud technology stack.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
- Problem Definition: Clearly defining the problem, aligning business goals and desired AI outcomes.
- Data Processing: Collect and clean datasets ensuring quality and readiness for modeling.
- Exploratory Data Analysis: Analyze data to identify patterns guiding feature selection.
- Feature Engineering: Leverage domain knowledge to develop features to boost model performance.
- Model Development: Implement machine learning algorithms to optimize model performance.
- Model Validation: Use appropriate metrics to evaluate model performance on unseen data.
- Model Deployment: Integrate the model into production systems for efficient operation.
- Monitoring and Iteration: Continuously track model performance and iterate based on feedback.
- Results Communication: Report insights and successes through real-time dashboards.
- Maintenance: Establish and manage the cloud environment using DevOps practices to ensure stability and scalability.
Qualifications
-
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
- OR equivalent experience.
- Strong grasp of ML concepts, able to explain both theory and practical applications.
- Proficient in NLP techniques, with demonstrated success in project implementations.
- Effectively translates academic knowledge into solutions for real-world problems.
- Skilled in data analysis using Python, Pandas, and Jupyter Notebooks or similar.
- Proficient in .NET or similar, with additional expertise in Python.
- Preferred experience in team-based development, utilizing Git for version control and managing release cycles.
- Azure Cloud Infrastructure: Familiarity preferred, but not mandatory.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
-
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical
- 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
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