Data Science @ Microsoft

Job Description

Are you a data scientist, and you love what you do Would you like to be a part of aglobalcustomer facing Teamfocusedon solving complex, real-world business problems Would you like to be a part of a community of technical leaders, highly specialised in their disciplines and working together as one to bring the best practices of engineering and architecture to worlds largest enterprise customers TheIndustry Solutions Delivery(ISD)Engineering & ArchitectureGroup(EAG) is a global consulting and engineering organization that supports ourmost complex and leading-edgecustomer engagements. EAG enhances ISDs technical capabilities, and partners withothers to develop approaches, innovativesolutions, and engineeringstandards to set our sales and delivery teams up forsuccess.Leveraging the principles of model, care, and coach, we provide consistent high-quality customerexperience throughtechnical leadership and IP capture centered on delivery truth. We are committed to. Responsible AI, and we help our customers and partners build ethical, transparent and trustworthy AI solutions. We are hiring aData Scientistwith experience in and passion for advanced statistical data analysis, and implementation of data science solutions in enterprises. You'll work with high-impact professionals to solve complex problems for strategic customers and partners. You'll communicate trends and innovative solutions and collaborate cross-functionally within the Microsoft ecosystem, including product teams, research, security, solution strategy, industry excellence, and responsible AI. Our team embraces a growth mindset and encourages diverse viewpoints. We value personal and cultural experiences and strive for excellence. We offer a flexible work environment to help you succeed in creating transformative and responsible AI solutions that positively impact billions worldwide. Responsibilities Business Understanding and Impact Leverages understanding of data science and business to examine aproject and consider factors that can influence final outcomes within a technical area. Evaluates project plan for resources, risks, contingencies, requirements, assumptions, and constraints. Documents key business objectives. Effectively communicates business goals in analytical and technical terms. Consistently shares insights with stakeholders. Data Preparation and Understanding Acquiresnecessary data for project completion and describes it using querying, visualization, and reporting techniques. Explores data for key attributes and contributes to development of quality reports. Collaborates with others to perform data-science experiments using established methodologies and tools. Partners with Solution Architects, Consultants, and Data Engineers in data preparation efforts. Identifies data integrity problems and adheres to Microsoft's privacy policy. Modeling and Statistical Analysis Applies machine learning knowledge to identify the best approach for project objectives, utilizing individual algorithms and modeling techniques. Selects the appropriate approach to prepare data, train, optimize, and evaluate the model for statistical and business significance. Writes scripts in SQL, Python, R, etc. Designs experiments, analyzes results, and communicates findings to stakeholders. Understands operational considerations for model deployment and partners with data engineering teams to develop operational models. Evaluation Understands the relationship between the model and business objectives. Tests models on test and production data, analyzes performance, and incorporates customer feedback. Reviews data analysis and modeling techniques to identify overlooked or reexamined factors. Contributes to the review summary. Industry and Research Knowledge/Opportunity Identification Learns and understands the current state of the industry, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Maintains knowledge of current trends within the discipline. Attends internal research conferences and participates in on-hands training, when appropriate. Actively contributes to the body of thought leadership and intellectual property (IP) best practices. Coding and Debugging Writes efficient and readable code for specific features, collaborating with other engineering teams to optimize code and improve system efficiency, reliability, and maintainability. Develops expertise in debugging techniques and integrates data models into customer systems. Understands big-data software engineering concepts, such as k, Databricks, CI/CD, Docker, Delta Lake, MLflow, Azure Machine Learning, and REST API consumption/development. Business Management Develops understanding of data structures and relationship to customer business goals, observes senior engineers for best practices in identifying growth opportunities and exploring ML applications. Understands customer business goals and demonstrates a strong commitment to Responsible AI, supporting customers, partners and internal stakeholders in building trustworthy AI solutions. Customer/Partner Orientation Focuses oncustomer needs, manages expectations, and enhances customer excellence. Learns from senior team members to develop insights and communicate results. Understands the impact of data quality on model accuracy and can explain it to customers. Other Embody ourcultureandvalues Qualifications Required/Minimum Qualifications Minimum of_4 years of experience as a data scientist implementing data science solution, with experience in implementing projects in one or more areas amongst: Computer Vision, LLMs, Audio/Voice data processing, and Reinforcement Learning. Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field AND 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, Engineering or related field data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, Engineering or related field OR equivalent experience. Your success in this role will be achieved if you are comfortable interacting with external customers, are able to manage a complicated internal stakeholder group, and can demonstrate the following key knowledge, skills and experience: Hands-on software engineering experience (e.g. Python, C++) Proven skills and experience in a data science role Familiarity with building and deploying largescale AI solutions into production within a cloud environment. Has experience in working with MLOps, LLMOps and frameworks like LangChain, Semantic Kernel and Prompt Flow.

Employement Category:

Employement Type: Full time
Industry: IT
Role Category: IT Services & Consulting
Functional Area: Not Applicable
Role/Responsibilies: Data Science

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Keyskills:   Machine Learning SQL Python R Debugging Software Engineering Data Scientist Advanced Statistical Data Analysis Data Science Solutions Model Deployment Big Data Software Engineering Responsible AI Customer Orientation MLOps LLMOps LangChain Semantic Kernel Prompt Flow