Sample Data Scientist Job Description
Who We Are
At Morgan McKinley, we never lose sight of the role we play connecting talent with opportunities to solve the problems of today and tomorrow. Every individual in our business strives to go beyond for our clients and candidates to provide expert advice and become the trusted partner of choice.
Wherever you work in our business, you will have the opportunity to bring new ideas to continuously improve our service and deliver real value to our customers.
Together we go beyond.
We help organisations build their talent capability. Connecting people with opportunities.
Improving lives - Our People. Our Clients. Our Candidates.
- Always embracing change
- Always committed
- Always communicating
- Always building trust
As a Data Scientist, you will use your quantitative skills to deliver actionable insights to a variety of senior external and internal stakeholders. Your innovative ideas will play a crucial part of driving cutting edge data approaches integrating client data and research with ML and AI to offer outstanding client outcomes.
You will be working in our Insight and Data team reporting directly to the Department Head.
- Developing and implementing predictive models and optimization algorithms that provides actionable insights
- Analysing data environment and develop a long-term data growth plan
- Identifying and analysing causes of urgent defects and making predictions on likelihood of recurrence
- Working with analytics partners to build and productionise models
- Effectively communicating with technical and non-technical stakeholders
- Acting as an internal consultant to the business on data driven decision making and insights
- Developing differentiated pricing models and educating stakeholders on findings
- Discovering trends and patterns within complex data and present findings to stakeholders
- Building analytical application designs and prototypes to test out ideas and drive innovation
- Producing creative data visualizations and intuitive graphics to present complex analytics to a non-technical audience
- Leveraging state-of-the-art data mining and machine learning tools and methodologies to drive improved business decisions
- Documenting and articulate key learnings from the data mining exercises
- 2-4 years commercial analytics experience (consumer product environment)
- Experience using SAS, SQL, R and/or Python
- Experience with Business Intelligence tools like Qlik/Tableau/Power BI is highly desirable
- Strong stakeholder management skills including advanced PowerPoint and presentation skills
- Exposure to Big Data technologies like Hadoop, Spark, Hive etc. is a plus
- Applied knowledge of data science techniques
- Hands-on experience in data mining and application of machine learning techniques
- Tertiary Qualification in a quantitative discipline involving strong statistics and or data
- Postgraduate qualifications and experience of machine learning
Hiring a Data Scientist?
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