Data Scientist II

• Discovering diverse content on the Web quickly and efficiently by understanding the structure and dynamics of the Web and optimizing crawl scheduling.
• Building Big Data pipelines, creating ML(Machine Learning) and AI models for index selection, and determining document quality.
• Designing and implementing models and pipelines for near-real time (NRT) indexing and content freshness.
• Designing and implementing methods for leveraging AI in platform and backend solutions.

This is a great opportunity for someone who loves to tackle deep technical challenges and strives for industry-wide impact. At this role, you'd be dealing with and learning how to do data collection, analysis and cleaning, building Big Data pipelines, making decision based on data, doing model training and deployment, and working with LLMs both for prompt engineering and fine-tuning.

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

• Acquire the data necessary for your project plan and use querying, visualization, and reporting techniques to describe that data. You’ll also explore data for key attributes and collaborate with others to perform data science experiments using established methodologies.
• Understand modeling techniques, select the correct tool and approach to complete objectives, and evaluate the output for statistical and business significance. You’ll also analyze model performance and incorporate customer feedback into its evaluation.
• Understand the current state of the industry, including current trends, so that you can contribute to thought leadership best practices.
• Write efficient code for a specific feature, and develop a working expertise of proper debugging techniques.
• Understand each customer’s business goals and learn best practices for identifying growth opportunities.
• Examine projects through a customer-oriented focus, and manage customer expectations regarding project progress.

Qualifications

Required Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical tec
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec
  • OR equivalent experience.
• 1+ year(s) customer-facing, project-delivery experience, professional services, and/or consulting experience.

Preferred Qualifications: 

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statist