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Machine learning engineering is a specialist role still in its infancy. Machine learning engineers collaborate with the organization’s data science team to build programs and create algorithms to deliver data-driven products and services that enable machines to make decisions, take action, and enhance user experience without any human interference. An example of this would be self-driving cars and personalized social media news feeds.

Machine learning engineers generally come from a mathematic, physics, or statistics undergraduate
background with a specialized master’s or PhD.

Data architects use extensive programming tools to design secure data frameworks in order to manage large electronic databases for organizations. This is a highly technical role that involves ensuring the data is relevant, accurate, and accessible to the organization so employees can access this information, such as financial records and marketing information, wherever and whenever they need it.

You’ll need superior analytical skills, an eye for detail, and sophisticated design skills as you fulfill the strategic needs of the organization.

Statisticians compile, analyze, and evaluate quantitative information from surveys and experiments in order to help organizations reach operational standards and advise on practical solutions to problems.

Relevant qualifications and industry experience are essential if you want to work in this field.

Data analysts are inquisitive, highly analytical, and have a way with numbers. Every organization and business collects data, whether it’s sales figures, logistics, market research, or transportation costs. As a data analyst, it’s your job to gather and evaluate this data in order to provide clear insights as to how the organization can improve its business strategy and make better business decisions across various areas.

This executive-level position demands an expert-level knowledge of technological trends and how they can be implemented in building business strategies. Chief technology officers are masters of strategic thinking and conducting technological analysis as they look at ways in which they can ensure the organization stands out in an ever-increasing competitive marketplace.

Strong leadership and organizational skills are essential in this role as you lead your team and consider which technologies are best to harness in order to ensure a positive user experience and efficiency across all areas of the business.

In 2012, only 12 percent of Fortune 1000 companies had a CDO. Within six years, 67.9 percent of surveyed firms reported having a CDO, according to . It is the chief data officer’s responsibility to strategically oversee the organization’s data and generate business value from what could be the organization’s most valuable asset.

Chief data officers are business-focused and have excellent expertise in IT. Relevant qualifications such as mathematics and statistics, plus a specialized master’s and industry experience, are all essential if you want to become a chief data officer.

In this fast-paced role, application architects need excellent technical vision, the ability to provide valuable insights and solutions to software development, use, and maintenance, as well as strong analytical, problem-solving, and critical-thinking skills.

Every day, they carry out a wide variety of tasks such as creating new and improved applications, developing prototypes, running software tests, and creating technical documents for application software. 

You’ll need proven programming language and architecture design skills and experience, as well as relevant qualifications and industry experience. A master’s in business analytics and big data, for example, will equip you with the ability to rethink and rebuild products, services, and processes as well as solve user problems using advanced analytics and relevant data insights.

As a project manager, you’ll use your data-driven business acumen to plan, budget, and oversee your organization’s project/s. You will also need to be organized and possess excellent leadership and critical-thinking skills.

Market research analysts compile complex reports, spreadsheets, surveys, and opinion polls in order to gather and evaluate significant market intelligence that can help an organization market their product or service in the best way possible. Data can include consumer demographics, spending habits and sales trends, needs, interests, and preferences.

Market research analysts need a good working knowledge of statistical software and techniques in order to monitor and forecast the effectiveness of such strategies.

As organizations continue to turn their attention to advanced and novel technologies such as artificial intelligence (AI) and machine learning to leverage success and improve business efficiency, business/analytics translators are filling the gap between an organization’s business team and technology team.

An organization’s business team and technology team can be at opposite ends of the spectrum, causing confusion, miscommunications, and in some instances, massive errors. Business/analytics translators work to ensure the focus stays on the organization’s values and objectives but are data-savvy enough to understand and liaise with those in the data science team. Business/analytics translators then confirm the ‘roadmap’ for going forward.

Using algorithms, artificial intelligence, machine learning, and other statistical tools, data scientists mine complex, raw data from a range of sources and turn it into meaningful, transparent information in order for the organization to improve their business strategy and operations.