Mapping Your Business Analytics Career Path: Opportunities, Skills, and Trends in 2026
The world of business analytics and data science is a uniquely exciting place to be in 2023. As an artificial intelligence and machine learning expert, I‘ve seen firsthand how the field is evolving at a rapid pace, creating a wealth of opportunities for professionals with the right skills and mindset.
In this guide, we‘ll take an in-depth look at the career paths available in business analytics today, the skills and knowledge required for success, and how you can navigate this dynamic landscape to build a fulfilling and future-proof career. Whether you‘re just starting out or looking to take the next step in your analytics journey, read on for expert insights and advice.
The Business Analytics Job Market in 2023
First, let‘s set the stage with some key statistics on the current state of the business analytics job market:
- The global big data and business analytics market is expected to grow from $198.08 billion in 2020 to $684.12 billion by 2030, at a CAGR of 13.5% (Source: Allied Market Research)
- The median annual wage for management analysts, a category that includes business analysts, was $93,000 in May 2021 (Source: U.S. Bureau of Labor Statistics)
- Job growth for management analysts is projected to be 14% from 2020 to 2030, faster than the average for all occupations (Source: U.S. Bureau of Labor Statistics)
- Data scientist and machine learning engineer were ranked as the #3 and #4 best jobs in the U.S. for 2023 based on salary, job growth, and job satisfaction (Source: Glassdoor)
These figures paint a picture of a field that is thriving and full of potential. But what exactly does a career in business analytics look like? Let‘s break down some of the most common roles and what they entail.
Business Analytics Career Paths
Business/Data Analyst
Business or data analysts are the backbone of many organizations‘ analytics efforts. They are responsible for collecting, cleaning, and analyzing data to uncover insights and inform business decisions. This can include:
- Identifying trends and patterns in sales, marketing, financial, and operational data
- Building dashboards and reports to track key metrics and KPIs
- Conducting ad hoc analyses to answer specific business questions
- Collaborating with cross-functional teams to implement data-driven changes
Example data analyst job description. Source: Zippia
According to Glassdoor, the average base pay for a data analyst in the US is $76,981 per year as of April 2023. Entry-level positions typically require a bachelor‘s degree in a quantitative field like business, economics, statistics, or computer science, along with proficiency in tools like Excel, SQL, and data visualization software.
Business Intelligence (BI) Analyst
BI analysts are similar to data analysts but tend to focus more on building and maintaining the systems and processes that enable data-driven decision making. This can include:
- Designing and building data warehouses and BI platforms
- Creating and managing ETL pipelines to integrate data from multiple sources
- Developing and distributing standard reports and dashboards
- Training and supporting business users on BI tools and best practices
BI analysts need strong technical skills, including experience with databases, query languages, and BI software like Tableau, Power BI, or Looker. They also need to have a deep understanding of the business to ensure that the right data is being collected and analyzed.
According to Payscale, the average salary for a BI analyst in the US is $70,936 as of April 2023. Senior BI analysts can earn upwards of $100,000 per year.
Common BI and data warehousing tools. Source: Analytics Vidhya
Data Scientist
Data scientists are the "rock stars" of the analytics world, using advanced techniques like machine learning and predictive modeling to extract insights from data. Their work can include:
- Identifying business problems that can be solved with data science
- Collecting and cleaning large, complex datasets
- Building and tuning ML models to make predictions or uncover patterns
- Communicating findings to technical and non-technical stakeholders
Data science roles typically require at least a master‘s degree in a field like computer science, statistics, or applied math, along with strong programming skills in languages like Python or R. Knowledge of big data technologies like Spark and experience with cloud platforms like AWS or Azure are also increasingly important.
Data scientist salaries can vary widely based on skills, experience, and industry, but the average base pay in the US is $120,092 per year according to Glassdoor as of April 2023. Top earners can command salaries of $200,000 or more.
The number of open data scientist jobs by country. Source: Quanthub
Analytics Manager/Leader
For those who want to move beyond hands-on analytics work and take on more strategic responsibilities, an analytics manager or leadership role may be the right fit. Analytics leaders are responsible for:
- Setting the overall analytics strategy and roadmap for their organization
- Managing and mentoring a team of analysts and data scientists
- Communicating the value of analytics to executive stakeholders
- Identifying opportunities to use analytics to drive business impact
Analytics managers need a strong foundation in both the technical and business sides of analytics, along with excellent communication and leadership skills. Many have at least 10 years of experience as an analyst or data scientist before moving into management.
Salaries for analytics managers can range widely depending on the size and type of organization, but the average base pay in the US is $142,957 per year according to Glassdoor as of April 2023.
Example analytics manager job description. Source: Aspirant Analytics
The Impact of AI and Machine Learning
No discussion of business analytics career paths in 2023 would be complete without mentioning the transformative impact of artificial intelligence and machine learning. As organizations collect and generate ever-larger volumes of data, AI and ML tools are becoming increasingly essential for extracting insights and driving efficiency at scale.
This has created a surge in demand for professionals with AI and ML skills, including:
- Data scientists and machine learning engineers who can build and deploy AI models
- AI ethicists who can ensure that AI systems are fair, transparent, and accountable
- AI product managers who can translate business needs into AI solutions
- AI translators who can bridge the gap between technical and business teams
According to a 2022 report by McKinsey, the number of available AI roles has grown by 74% over the past four years. The median annual wage for AI and ML specialists in 2023 is $158,587 (Source: Datamation).
The growth of AI patents granted by year. Source: Atlas of AI
To succeed in this new landscape, business analytics professionals need to be proactive about developing their AI and ML skills. This can include:
- Taking online courses or pursuing certifications in AI/ML techniques and tools
- Applying machine learning to real-world analytics problems
- Collaborating closely with data science and engineering teams
- Staying up to date on the latest AI/ML research and best practices
The Rise of Analytics Translators
As the technical complexity of business analytics grows, there is an increasing need for "analytics translators" who can bridge the gap between data scientists and business stakeholders. Analytics translators are individuals who have a deep understanding of both the technical and business sides of analytics and can facilitate communication and collaboration between the two.
According to a report by McKinsey, analytics translators "are neither data architects nor data engineers. Instead, translators play a critical role in bridging the technical expertise of data engineers and data scientists with the operational expertise of marketing, supply chain, manufacturing, risk, and other frontline managers."
Key skills for an analytics translator role. Source: Author
Some key skills and characteristics of successful analytics translators include:
- Strong business acumen and industry knowledge
- Familiarity with analytics techniques and tools, but not necessarily deep technical expertise
- Excellent communication and stakeholder management abilities
- Ability to think strategically and tie analytics initiatives to business outcomes
- Collaborative and cross-functional mindset
The demand for analytics translators is growing rapidly as organizations seek to extract more value from their data investments. According toone analysis, the number of analytics translator job postings surged by over 200% between 2020 and 2022.
Choosing the Right Analytics Career Path
With so many different business analytics career paths available, it can be challenging to determine which one is the best fit for your skills, interests, and goals. Here are a few key factors to consider:
- Your technical skills and aptitudes (e.g. statistics, programming, databases)
- Your business domain knowledge and industry interests
- Your communication and collaboration abilities
- Your desired level of hands-on technical work vs. strategic responsibilities
- The size and type of organization you want to work for (e.g. large enterprise, startup, consulting firm)
Here‘s a quick comparison of some common analytics roles:
| Role | Technical Skills | Business Skills | Strategic Focus |
|---|---|---|---|
| Data Analyst | Moderate | Moderate | Low |
| BI Analyst | High | Moderate | Low |
| Data Scientist | Very High | Low | Moderate |
| Analytics Manager | High | High | High |
| Analytics Translator | Moderate | Very High | Moderate |
Remember, there is no one "right" path in analytics – the key is to find a role that aligns with your unique blend of skills and interests and provides opportunities for growth and impact.
Getting Started in Analytics
If you‘re looking to break into the field of business analytics, here are a few tips to get started:
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Develop your foundational skills in statistics, data analysis, and programming through online courses, bootcamps, or degree programs. Some great resources include:
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Gain practical experience through internships, projects, or volunteer work. Look for opportunities to work with real-world data sets and business problems.
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Network with other analytics professionals through events, conferences, or online communities. Some great options include:
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Consider pursuing certifications to demonstrate your skills and stand out to employers. Some top certifications in the field include:
Advancing Your Analytics Career
Once you‘ve landed your first analytics role, there are many paths you can take to advance your career over time. Here are a few strategies to consider:
- Develop deep expertise in a particular business domain or industry vertical
- Expand your technical skills in areas like machine learning, cloud computing, or data engineering
- Take on project management or team leadership responsibilities
- Pursue a graduate degree in analytics or data science
- Transition into an analytics translator or executive role
- Start your own analytics consulting business or startup
The most important thing is to stay curious, continuously learn, and proactively seek out new challenges and opportunities. With the right skills and mindset, the possibilities for growth and impact in the world of business analytics are truly endless.
