Find data science roles in any industry
Many graduates have curiosity in data science. However, aside from tech companies, they may be uncertain where such opportunities lie. Fortunately, the number and variety of analytical roles are vast and ever-expanding. Below is an overview of companies and industries that have roles in data science.
Corporations. These are household name companies — AT&T, Capital One, P&G, Nike. These companies generally have analytics teams within the marketing, business strategy, operations, and finance business units. Data and analytical processes vary depending on the industry. However, these companies can be a good foundation for an analytical career because they (a) have access to massive and varied forms of data and (b) have well-developed analytical infrastructures and processes.
Consulting Firms. Several traditional strategy consulting firms are moving into big data, so it’s possible to find roles at consultancies as a data scientist. These roles generally require analysts to be eloquent and strategically-minded. No matter how technical the position, expect to present your work to extremely smart, senior audiences. These roles often require a technical Masters' and/or previous business experience.
Market Research & Mixed Modeling. These firms use complex regression models to optimize large companies’ marketing budgets — we’re talking tens of millions of dollars in marketing budgets. Therefore, these companies require technically strong and business savvy data scientists to generate recommendations from these models.
Ad Agencies. These companies buy media for corporations. Analytics teams do work such as marketing mix, attribution, and social media analytics. However, a cautionary note — analytics at these firms are often not as well received by clients, compared to consulting or market research firms. This is because consultancies act as 3rd party arbiters of a clients’ marketing budget, whereas the ad agencies are direct beneficiaries of marketing budgets, causing a perceived conflict of interest.
Ad Tech. These companies, often startups, are on the front line of digital marketing innovation. Modern digital marketing leverages massive amounts (terabytes on terabytes) of data pulled from cookies across the internet. Analysts and back-end programmers at these companies may use a platform such as Hadoop or Spark to process data and statistical models to create “look-alike” or purchase-intent models. These companies also require less technical but still technically-minded people to translate their products’ processes to their clients.
Big Data Vendors. These companies satisfy a wide range of big data requirements, but generally fall into 3 buckets:
- Data Processing Services (e.g. Oracle, SAS, AWS) who provide the infrastructure to execute big data analytics.
- Data Visualization Services (e.g. Tableau and Looker) who provide business intelligence tools that manage and/or connect to enterprise databases.
- Data Analytics Services (e.g. ClickFox and 1010 Data) help companies aggregate and analyze companies’ 1st and 3rd party data. These companies are akin to consulting analytics companies.
These companies require programmers and highly technical data scientists to build their products’ infrastructures; however, they also need analysts with business intelligence and presentation skills to help sell & integrate their products into their clients’ businesses.
Tech Companies. Google, Facebook, LinkedIn, Amazon — these are the types of companies where you’ll find some of the most talented data scientists. These companies compensate their data scientists well above the industry average, but they often require computer science and mathematics backgrounds from leading universities. The reason these companies require more skilled analysts is because their processes generally impact the company’s product — for instance: Amazon & Facebook’s recommendation engines and Uber’s route optimization algorithms) — as opposed to customer analytics & marketing.
Start Ups. Almost every startup company will require analytically talented employees. Early stage companies (i.e. those with 50 employees) often manage analytics with marketers who use 3rd party SaaS tools or with programmers who have some business acumen. Therefore job-seekers should look for startups with 60–150 employees, as that is a sweet spot where companies will begin moving into more robust analytics.
Financial Firms. Opportunities in finance are abundant as they are diverse. Roles can range from credit risk analysis at credit card (or other financial) companies to trading algorithm engineers at hedge funds. These roles generally require a computer science and/or mathematics background and previous experience in finance; however, roles exist that aren’t inherently financial, such as business intelligence.
Final Thoughts
We tend to have narrowly-defined views of the companies where data scientists work, assuming that most roles exist within tech. However, this is far from the case. Data science jobs cut across nearly every industry and can be found at a variety of companies. Also, by moving across industries and specializations, data scientists can deepen their general understanding of how to apply data science anywhere in the world!
