Senior Data Scientist
Microsoft
Senior Data Scientist
Melbourne, Victoria, Australia
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Overview
Do you enjoy solving problems, looking at challenges through a different lens, and working closely with customers to innovate new solutions to complex problems? Do you jump with excitement at the opportunity to identify trends and provide unique business solutions? Do you want to join a team where learning about a new technology or solution is part of our work every day?
The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges. We work closely with our customers’ engineers and data scientists to jointly develop code for cloud-based solutions that can accelerate their organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more with the cloud. We pride ourselves in making contributions to open source and making our platforms easier to use.
We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. In this role, you will be working with engineers and data scientists from your team and our customers’ teams to apply your skills, perspectives, and creativity to grow as engineers and data scientists and help solve our customers’ toughest challenges.
We are hiring a Data Scientist with deep experience in developing and employing statistical and machine learning techniques to deliver business results. As part of our team, you will be working side-by-side with high-impact engineers and data scientists and strategic customers to solve complex problems. You will work cross-functionally with several teams including software engineers, data scientists, product teams, and program management to deploy business solutions.
Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!
Qualifications
Required Qualifications:
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., applying statistical techniques, building and evaluating machine learning models, deploying models to production, maintaining models in production and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., applying statistical techniques, building and evaluating machine learning models, deploying models to production, maintaining models in production and reporting results)
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., applying statistical techniques, building and evaluating machine learning models, deploying models to production, maintaining models in production and reporting results)
- OR equivalent experience.
Preferred Qualifications:
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., , applying statistical techniques, building and evaluating machine learning models and reporting results)
- OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., applying statistical techniques, building and evaluating machine learning models, deploying models to production, maintaining models in production and reporting results)
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., applying statistical techniques, building and evaluating machine learning models, deploying models to production, maintaining models in production and reporting results)
- OR equivalent experience.
- Experience working as part of geographically dispersed, diverse, and virtual teams
- Enjoy travel and are comfortable with travel up to 25%
- Demonstrated ability to work with customers and collaborate across company boundaries.
- 3+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!
At Microsoft, we are seeking people who have a passion for the positive impact technology can have on communities and for making a difference in the world. Within ISE, you will find a wide range of backgrounds, perspectives, personal and cultural experiences which are vital to our success with our customers. It’s an informal and flexible work environment and you’ll be welcome to work in the way that best enables you to get your job done.
We invest in your health, wellness, and financial future by offering a competitive package including a wide range of benefits built around your personal needs and those close to you.
#ISEngineering
#WSS
Responsibilities
Business Understanding and Impact:
- Contributes to the adoption of good practice on engagements that employ data science to align with business needs and deliver value. Can articulate the objective of an engagement in both technical and business terms and provide clear linkage between these.
- Works closely with software engineering and business stakeholders on tasks to include artificial intelligence and machine learning in systems development. Contributes to the prioritisation of work to be undertaken in the engagement.
Data Preparation and Understanding:
- Acquires data necessary for successful completion of the project plan. Proactively detects changes and communicates these to engagement leadership.
- Builds usable data sets and assets for modelling purposes and contributes to the building of repeatable processes and pipelines to support data acquisition.
- Contributes to ethics and privacy policies related to the collection and preparation of datasets.
Modelling and Statistical Analysis:
- Has deep and demonstrated understanding of machine learning techniques, including the algorithms and modelling techniques used to deploy production grade machine learning and artificial intelligence solutions.
- Demonstrated experience evaluating and selecting from multiple modelling approaches and automation of these solutions.
Evaluation:
- Employs appropriate data analysis and modelling techniques. Ensures selected modelling techniques are appropriate and align with desired project outcomes.
Industry and Research Knowledge/Opportunity Identification:
- Provides feedback, drives improvement, and shares knowledge as a data science practitioner. Contributes to ongoing team learning by bringing relevant and leading edge concepts and approaches to the teams attention.
Coding and Debugging:
- Leads by example in contributing code, artefacts, and guidance during the execution of engagements. Writes and debugs code for complex projects. Delivers production quality code in association with software engineers. Employs appropriate approaches to considering security throughout an engagement.
- Has a good grasp and ability to apply core software engineering principals.
- Coaches and mentors junior data scientists.
Business Management:
- Collaborates with end customer and Microsoft internal cross-functional stakeholders to understand business needs. Formulates a roadmap of project activity that leads to measurable improvement in business performance metrics over time. Influences stakeholders to make solution improvements that yield business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools. Exemplifies and enforces team standards related to bias, privacy, and ethics.
Customer/Partner Orientation:
- Confirms the business outcomes are feasible and practical and links the approach employed to the business outcomes. Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.