Azure Lead Data Scientist

Responsibilities

• Leveraging advanced analytics techniques and tools such as Azure Machine Learning, Azure Open AI, Azure AI Search, Azure Synapse Analytics, Databricks, and Power BI
• Extract insights from large datasets and develop data-driven solutions.
• Lead end-to-end data science projects, collaborate with cross-functional teams, and stay updated with emerging Microsoft technologies.
• Strong problem-solving, programming, and communication skills.
• Building predictive models and other analytical solutions.
• Apply statistical and machine learning methods to analyze large, complex data sets.
• Collaborate with various parties to brainstorm creative uses for data.
• Develop complex algorithms and statistical predictive models and determine analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.
• Perform analyses of structured and unstructured data to solve multiple and complex business problems.
• Deliver actionable guidance and recommendations to stakeholders to help understand nuances of the models built and tactics for improving.
• Act as the subject matter expert on solutions produced by working closely with your peers to help Clients better understand their data.
• Actively participate in the execution and planning of data capture strategies to improve data automation, data quality, and analytics capabilities.
• Run ad-hoc data extracts for requests from diverse partners and automate those needs over time.
• Perform highly complex, technical, and creative predictive analytics projects.
• Manage and prioritize multiple moderate-to-highly complex projects including gathering business requirements, developing project goals and requirements, coordinating project timelines, and communicating project status and deliverables with Clients.
• Stay abreast of architectural/industry changes in related fields.
• Continuously improve Team processes to ensure information is of the highest quality, contributing to the overall effectiveness of the Team.
• Ensure best practices are followed and business objectives are achieved by focusing on process improvements.
• Meet with Clients to determine needs and/or identify problem areas.
• May be responsible for the development of Statement of Work and Proposals which outline professional services required to meet Client requirements.
• Must be open to ~10% travel on an as needed basis.

Qualifications

• 7+ years of hands-on experience with data science, AI, and big data. Experience with data engineering is a plus.
• Degree in Information Technology or Business Administration or equivalent combination of education and experience
• Experience developing and owning production-level models using various data sets.
• Experience shipping models to production, and ensuring continuous availability via measurements, and tools like statistical process control.
• Ability to translate business needs into technical requirements through active partnerships, collaborating with partners, data scientists and data architects.
• Compelling storytelling through analytics and visualization, getting your point across, and keeping your audience engaged.
• Experience working in Python, R, Scala, Spark, and/or T-SQL.
• Extensive experience connecting to Data Platforms including data lakes, data warehouses, NoSQL databases, and APIs.
• Ability to set up data and experimental platforms.
• Strong critical thinking, active listening, and communication skills to infer business needs, grasp the underlying context, and translate loose direction on analytical projects into concrete solutions.
• Attention to detail and desire for end-to-end ownership of deliverables.
• Experience working on projects involving large volumes of data, preferably in the Manufacturing industry.
• Demonstrates the ability to communicate effectively with technical teams, business stakeholders, and other relevant parties