Data Scientist

Key Skills

AI technology, Apache Hadoop, C++, Continuous Integration & Continuous Delivery - CI/CD, Data science techniques, Docker, Machine learning techniques, Python Programming

Job Description

Overview

Are you an experienced Data Scientist, and you love what you do? Would you like to be a part of a global customer facing Team focussed on 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 team to bring the best practices of engineering and architecture to the world’s largest enterprise customers?

We are hiring a Data Scientist with experience in advanced statistical data analysis to work with high-impact professionals who are solving complex problems for strategic customers and partners. You'll enhance your communication skills as you share trends and innovative solutions, collaborating cross-functionally within the Microsoft ecosystem, including with product teams, research, security, solution strategy, industry excellence, and responsible AI.

The Industry Solutions Delivery (ISD) Engineering & Architecture Group (EAG) is a global consulting and engineering organisation that supports our most complex and leading-edge customer engagements.  EAG enhances ISD’s technical capabilities, and partners with others to develop approaches, innovative solutions, and engineering standards to set our sales and delivery teams up for success.  Leveraging the principles of model, care, and coach, we provide consistent high-quality customer experiences through technical leadership and IP capture centred on delivery truth. We are committed to Responsible AI, and we help our customers and partners build ethical, transparent and trustworthy AI solutions.

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.

Read more about the culture and values we demonstrate.

Qualifications

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
• Regular interaction with internal and external stakeholders on large, complex projects
• Bachelor's or Master’s degree in data science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or equivalent data-science experience

Responsibilities

As a Data Scientist, you will be responsible for creating and deploying AI solutions that are ethical, reliable, and enable our customer to create impact. Some of your key responsibilities will include:

• Engaging with stakeholders to understand and address their business problems with data-driven solutions. 
• Writing clear, efficient code for multiple features, with expertise in modelling, coding, and debugging.
• Proficiency in big-data engineering concepts like Hadoop, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, AML, and REST API development. 
• Using your data science expertise to identify factors that influence project outcomes.
• Preparing usable datasets for modelling, contributing to ethics and privacy policies around data collection.
• Leveraging machine learning knowledge to select appropriate solutions for business objectives.
• Overseeing AI use case implementation and coaching cross-functional teams
• Writing scripts and conducting controlled experiments with statistical analysis, communicating results to stakeholders.
• Partnering with data engineering teams for scalable operational models.
• Sharing industry insights via conferences and publications, staying updated on trends and contributing to thought leadership and intellectual property practices. 
• Mentoring junior engineers and data scientists in best practices.