Decision Scientist

Advanced Analytics

Job Family

AU$140K

Salary

Average salary in Australia

22%

Job Growth

Open Roles

Job openings on Alooba Jobs

Decision Scientists use advanced analytics to influence business strategies and operations. They focus on statistical analysis, operations research, econometrics, and machine learning to create models that guide decision-making. Their role involves close collaboration with various business units, requiring a blend of technical expertise and business acumen. Decision Scientists are key in transforming data into actionable insights for business growth and efficiency.

What are the responsibilities & duties of a Decision Scientist?

Develop and analyze models to quantify credit loss.
Create predictive models for various business scenarios including financial, operational, and customer engagement.
Apply traditional statistical techniques and mathematical concepts to business problems.
Build large, efficient datasets for Decision Science applications, optimizing for speed and automation.
Perform data mining and trend analysis to develop segmentation strategies.
Partner with marketing and other teams to support data-driven decision making.
Produce data visualizations to communicate findings to internal stakeholders.
Research and develop decision science models, providing consultancy to business units.
Manage complex data processing and system validation tasks.
Build and maintain advanced decision science algorithms and tools.
Act as a peer leader and guide junior colleagues in technical methodologies.
Contribute to analytics innovation and integration within the organization.

What are the required skills & experiences of a Decision Scientist?

2+ years of experience in a quantitative field such as Data Science or Decision Science.
Bachelor's degree in a relevant technical field or equivalent practical experience.
Proficiency in statistical modeling and data analysis (e.g., regression, time series).
Experience using Python or R for statistical modeling.
Strong SQL skills for data querying and manipulation.
Excellent analytical, problem-solving, and communication skills.
Ability to work independently and collaborate with cross-functional teams.
Knowledge in various analytical fields such as Bayesian statistics, optimization, econometrics, and machine learning.
Familiarity with software development and cloud computing tools.
Strong business acumen and ability to translate data insights into actionable business strategies.

Discover how Alooba can help identify the best Decision Scientists for your team

Decision Scientist Levels

Intern Decision Scientist

An Intern Decision Scientist is a budding professional who uses data analysis, machine learning, and statistical modeling to inform strategic decision making. They are keen learners, ready to apply their academic knowledge to real-world business challenges, and are instrumental in supporting the organization's data-driven initiatives.

Graduate Decision Scientist

A Graduate Decision Scientist is an early-career professional that uses data, statistical methods, and business acumen to make informed decisions. They apply their academic knowledge to real-world challenges, providing valuable insights that drive strategic decision-making. Their role is crucial in supporting data-driven business operations.

Junior Decision Scientist

A Junior Decision Scientist is a budding professional who applies a blend of data analysis, statistical modeling, and business acumen to inform strategic decision-making within an organization. They play a crucial role in transforming complex data into actionable insights, contributing to the organization's data-driven initiatives.

Decision Scientist (Mid-Level)

A Mid-Level Decision Scientist is an analytical professional who leverages data to drive strategic decisions within the organization. They apply statistical modeling, machine learning algorithms, and analytical reasoning to provide data-driven insights that influence business strategy. They are key players in the organization's decision-making process.

Senior Decision Scientist

A Senior Decision Scientist is an expert in leveraging data to drive strategic business decisions. They apply advanced analytical and statistical techniques to solve complex business problems, guide strategic initiatives, and influence organizational decision-making. Their expertise lies in transforming data into actionable insights and foresighted strategies.

Lead Decision Scientist

A Lead Decision Scientist is a strategic leader who uses data-driven insights to guide decision-making processes. They leverage their expertise in data science, analytics, and business strategy to shape the direction of the organization. Their role is pivotal in turning complex data into actionable strategies that drive business growth.

Common Decision Scientist Required Skills

Over 50,000 Candidates Can't Be Wrong

Everything went very well - I liked the structure of this test and everything was relevant to the job

Ling

Data analytics candidate for leading graphic design software business

The website itself was amazing, and I liked it more than any LinkedIn or other assessment I took before. It shows how seriously you are taking this and made me enter the test mode without being stressed.

Majed

Marketing analyst candidate at Asian travel giant

The test is designed very well where it tests you different aspect of data comprehension. From data reading, data analysis, Excel formula, inference, and pattern recognition. The free response test is very interesting where it is simple enough to test your communication skill.

Raymond

Marketing strategy senior candidate for global travel company

I like the way of getting into this new job i think its a very complete assessment i like it a lot! Thanks for the opportunity

Nicolas

Sales development rep for tech startup

Our Customers Say

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

We get a high flow of applicants, which leads to potentially longer lead times, causing delays in the pipelines which can lead to missing out on good candidates. Alooba supports both speed and quality. The speed to return to candidates gives us a competitive advantage. Alooba provides a higher level of confidence in the people coming through the pipeline with less time spent interviewing unqualified candidates.

Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)