Three data engineer walk into a bar. Barkeep says, “Do you all want cocktails?” First data engineer says, “I don’t know,” second one says, “I don’t know,” third one says: “Yes.”
The candidate we’re looking for here is just as highly attuned to flawed assumptions as our heroes above, but also speaks the bartender’s vernacular and could easily explain to him the logical problem with the way he delivered his question (Warning: In real life, this does not result in attentive service). That rare combination allows one to build highly accurate and responsive machine-learning products while communicating easily and clearly with stakeholders who don’t happen to share that analytical bent — a skillset sure to be well rewarded by this big-and-getting-bigger television company.
Nitty Gritty
The essence of the work is turning data into useful knowledge, helping the people in sales, marketing and business development make wise decisions backed by the numbers. Instead of just spewing out figures, you’ll sympathize with each area’s needs and think creatively about how to solve their problems through data.
The data sets will come from various sources, some internal, some external and some hand-built by you yourself. Some will be structured, some unstructured. You’ll create data pipelines, dashboards and alerts. Much of your pattern-identification and segmentation work will be integrated into production applications to improve the audience’s experience (Think: “You may also like,” or promotional messaging). And, as alluded to above, you’ll do a good deal of communicating with people on the programming, business, sales and marketing sides to find out what they need, to guide them in asking the right questions the right way, and to share the killer insights you’ve developed.
Hired Gun Profile
About half a decade is how long you’ve been in the game, having launched out of a college program focused on statistics or analytics. You have an exceptionally deep familiarity with various strategies for classifying data, and otherwise-talented-enough colleagues go green with envy at the ease with which you can extract, map and script data from any kind of database, from the gargantuan down to the sparse. Data experiments and iteration are right up your alley, as are real-time stream analysis, algorithms and machine learning techniques. As for the tools at your disposal, there isn’t much you can’t wield to devastating effect– SQL, JQL, NoSQL, Python, asR, SPSS, Pentaho, Tableau, Kx, Tensorflow. You are . . . ninja.
Inside Skinny
This outfit will only hire someone fully committed to the science and completely up to date on the latest tools and techniques.
Net Net
It’s a great time to join this team of super-talented folks who are increasingly willing to direct resources to the kinds of innovation that only someone like you can help them pull off.
All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, creed, age, sexual orientation, veteran status, marital status, disability, or any other status protected by applicable law.
