Machine Learning

Job Description

• The opportunity to take on some of the worlds most meaningful challenges, helping customers achieve clean water, safe food, abundant energy, and healthy environments
• The ability to make an impact and shape your career with a company that is passionate about growth
• The support of an organization that believes it is vital to include and engage diverse people, perspectives, and ideas to achieve our best

Role & Responsibilities:

• Actively engage with internal technical and business teams to architect analytics-enabled digital products that deliver insights, predictions, and optimization outcomes, at scale. Lead their ongoing evolution.
• Work alongside IT & engineering groups to leverage cutting edge technology (machine learning platforms, streaming analytics, and real big data) to efficiently deploy data science algorithms, statistical models, and analytical solutions into production
• Own responsibility for the Model Development Life Cycle. Guide your team to set up the environment, design CI/CD pipeline, test & optimize the code, manage model repository & deployments.
• Network and collaborate with a broad range of internal business stakeholders to define and deliver joint solutions.
• Create, maintain and document a robust set of metrics to monitor day-to-day bug detection and long-term performance tracking.

Required Technical Skills for the Candidate

• Knowledge of Microsoft Azure Suite - Azure ML Studio, Azure Data Factory, Power BI/Power Apps
• Experience working with large datasets (several Gigs), using cloud-hosted leading industry platforms or proprietary data science modeling/model deployment software
• Experience leading teams of machine learning engineers & data science personnel engaged in constructing high-performance analytical models using Python/R scripts, ML libraries, Jupyter notebooks.
• Experience in leading design/build of scalable data analytics products/solutions at an enterprise level
• Good understanding of data science model deployments on CI/CD pipelines (specifically Kubeflow); and build/deployment of portable scalable machine learning workflows based on Docker containers
• Hands-on experience working with (any one of): AWS, Google Cloud, Microsoft Azure cloud orchestrations.
• Hands-on experience building out reports on Visualization tools (any of) Tableau, Qlik, Power BI.
• Hands-on experience working with (any one of) database formats: Oracle, SQL Server, DB2, MySQL, Teradata

Background of the ideal candidate

• 10+ years of IT work experience with 5+ years in data engineering/data science roles
• Bachelors degree in Engineering, Math, Science, Statistics, Data Analytics, or Computer Science
• Excellent communication, people management, and leadership skills
• A problem-solving, hands-on mindset. One who can quickly toggle between, diving deep into code to solve a team members technical challenge, and zooming out to think strategically about the solutions being created.
• An independent technical leader who can define new approaches to problems and lead a project development team.
• An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice, meanwhile embracing the full product lifecycle for digital data science.
• The ability to explain complex mathematical solutions in a simple & eloquent manner that most will understand, including customers.
• A team mentality, empowered by the ability to work with a diverse set of individuals, understand and deliver cross-functional requirements to enable holistic customer solutions.
• A focus on scalable development, adhering to best practices for efficient coding and architectural design.
• Ability to champion recommendations and influence decisions at the senior management level
• Ability to establish effective cross-functional partnerships and relationships at all levels in a highly collaborative environment
• Strong experience in handling multi-national client engagements
• Excellent Communication, Interpersonal, people management skills
• Ability to structure and deliver presentations clearly, crisply, and compellingly

Keyskills :
microsoft azureawsmachine learning