Taking Responsibility for Your Analytics Career
Analytics roles are many and varied. However, whether you are currently a Data Analyst, Data Scientist or Business Analyst, there are some useful ways of thinking about potential career paths that apply to all.
Broadly speaking, there are three types of medium-term career paths that analytics professionals typically follow:
- Advancing within analytics
- Switching to “adjacent” roles
- Switching to more business-oriented roles
1. Advancing within analytics
If your aim is to stay within the world of analytics a key choice will be whether you wish to remain an individual contributor or a manager. The former focuses on solving particular technical aspects of data analytics and aims, over time, to offer technical leadership to the teams he/she works within. The latter on the other hand will, over time, manage larger and larger teams of people, providing leadership and enabling team success, but inevitably moving further and further away from actually “doing” analytics.
A common career path within data science might be Junior Data Analyst / Business Analyst -> Data Scientist -> Senior Data Scientist -> Lead Data Scientist -> Principal Data Scientist / Director of Analytics.
An individual contributor might max out at Senior Data Scientist and thereafter be called upon for subject matter expertise. Lead Data Scientists and above will be managing projects end-to-end and, ultimately, organisational units.
2. Switching to “adjacent” roles
Because data manipulation and coding can form such a large part of the role of a Data Scientist, many analytics professionals discover a real passion for data and / or software engineering and steer their career paths in this direction. Typical adjacent roles can be as a Data Engineer or as a Software Engineer (e.g., for machine learning or backend systems or even full-stack). The analytics / data science career path is replaced by an engineering one within IT.
3. Switching to more business-oriented roles
For those drawn to the business side of things, a common route is into Product Management of data products – products which are intrinsically analytic in nature (e.g., a customer propensity to churn model, or an inventory stock-out likelihood model). Data driven decision making, telling stories through data, interpreting A/B tests, etc. are all transferable skills from analytics roles into product management.
Product management is an attractive route for many since, in time, the role demands a much wider skillset. You have to identify business needs, develop a product concept and bring it to market. You may need to manage Marketing Strategists, Product Managers, Change Managers, Data Scientists, and Engineers. (Incidentally, all of these roles are viable destinations for Data Scientists!)
Moving into the business need not only be via product management. Become an expert in the data and analytics aspects of the part of the business that most intrigues you (e.g., digital marketing, supply chain, finance, HR, etc.). Remember that data and analytic fluency is in short supply in most business functions so make contacts and look for an opening to get started.
Being aware of the variety of paths available to you is an important first step on the road to shaping your analytics career. Understand your own strengths and interests, get enough exposure to the different domains to identify your preferred destination and then plot your route to success!