Azure Lead Data Scientist

Title Senior Data Scientist

Location Virtual, home based office with travel

Description

The Senior Data Scientist is responsible for being a partner to team members, a mentor, and directly enabling growth of the Manufacturing Intelligence team at MCA. The Sr. Data Scientist is expected to lead Data Science implementations, drive innovation, upskill and mentor junior teammates, and partner with leadership to drive continuous improvement.

Within a project framework, the Sr. Data Scientist is responsible for building client relationships, effectively utilizing Agile project delivery methodologies, implementing scalable and efficient technical architectures to satisfy client requirements, and performing hands on implementations of Microsoft data solutions for MCA Connect’s current and future customers/projects.

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