Suggestions
Gokhan Ciflikli
Senior Data Scientist at Attest
Gökhan Çiflikli is a senior data scientist with expertise in statistical inference, predictive modelling, machine learning, and explainable AI.
He is a member of the Quanteda Initiative, a UK non-profit organization dedicated to open-source text analysis software, and also serves as a lecturer for the LSE Summer School course 'Introduction to Data Science and Machine Learning (ME314).'
Prior to his current role at Attest, a leading consumer insight platform, Gökhan held research positions at prestigious institutions such as LSE, UCL, and Uppsala University.
At Attest, his focus lies in automating data quality and audience checks, utilizing anomaly detection algorithms to identify and eliminate survey fraud such as impossible demographic combinations and bot-like behavior.
He collaborates cross-functionally with software engineers, product managers, and designers to create algorithmic solutions that reduce manual intervention and deliver actionable insights to clients.
Gökhan is actively involved in developing the core data science library, crafting bespoke Python modules, and providing guidance on data science best practices for product managers and engineers.
Additionally, he mentors junior team members and visiting Faculty fellows, gives technical talks, and organizes educational sessions to democratize data science within the company.
Highlights
I consider myself a technical middle manager.
As in, I'd like to think(!) I am quite capable of writing end-to-end production grade code for ML/AI projects.
Most of my managers have been technical as well, architecting and churning out code quite frequently.
However, it is always a tricky line to walk.
Unless you are at an early stage startup or a true outlier w.r.t. coding ability within the org, #coding at #leadership level primarily satisfies your own preferences with disproportionate downsides for your function.
A good IC, amongst other things, can
- write good code
A good middle manager can
- identify exec sponsorships
- manage stakeholders
- manage change
- establish vision
- chart strategy
- line manage leads and ICs
- build career growth frameworks
- be a 💩☂️ for their team
If you neglect your primary responsibilities just because you want to roleplay as an IC, you are doing your team a great disservice. Others can code; no one can do your job. The opportunity costs are too damn high✊
Link to this week's TeamCraft issue in the comments🗞️
#tech #management #datascience #dataengineering
Bought Vin Vashishta's book after seeing his post reflecting on an unfavourable review (always a good play).
When I ordered it Amazon, it was tied at one anonymous negative review vs. Stuart Winter-Tear's quite positive review. Now it's tied 2-2, with a clear divide across the pond - US folks not liking it as much as UK peeps - wonder if there's a pattern there (alas, small n).
As much as I like reading technical stuff, I also try to keep abreast of data strategy, vision, and ROI books on the market. If you have seen my posts, you know that I praise Simon Asplen-Taylor's book (Data and Analytics Strategy for Business) all the time - it tangibly improved the way I run my data departments 🙌🏻
Here's to hoping for another gem of a 📖 - I know sometimes people push back on them but I do enjoy Vin's LI posts; for me opinionated >> bland. As Naval Ravikant says, no one can beat you at being you, so you gotta play to your strengths and let your personality shine through.
