Insights From Hiring Managers on Resumes
Our specialization, Tailoring Your Resume, Demonstrating Work Exp, ATS Optimization, Resume to interview
I made a post on what to do when making your resume. But, I never addressed what the process is like from the other side. When your resume, and 100+ resumes show up at our desk, what do we do next?
How do we separate those who will get an interview, and those who will get their resume tossed? This post is here to answer that question. I collaberated with
to make this post. He knows his stuff, go check him out.Table of Contents:
What we hire (our specialization)
Tailoring Your Resume
Demonstrating Work Experience
ATS Optimization
How Your Resume translates to the interview
1.1 BowTied_Raptor
I’m a person who specializes in hiring Machine Learning Engineers, and Quants. A few years ago I started off as a simple data analyst. I then “earned a voice” within my industry, and now hire both Quants and MLEs.
I’m generally working next to the team lead/product manager. There are two main things I do on a daily basis.
I am improving a quant model. I test it to see how well it works in different situations, like when things around us are changing.
I work with the product manager to coordinate tasks with other members in the data team.
I am not have the title of a “hiring manager” as of now. But, I’ve earned the trust of most key decision makers to the point where… I have the final say in who gets hired, and who doesn’t.
1.2 BowTiedWhiteblt
My name is bowtiedwhitebelt. I’m a technical product manager by trade & writer of Pivot to Product. Many years ago, I was presented with the opportunity to specialize in the product world as a “Data Product Manager”. Since that day, I’ve risen up the tech corporate ladder in tech, and now find myself as my company's Data & Analytics lead. I now, have a team of data analysts, data scientists, and data product managers who all report to me.
It’s my job to forecast the headcount needed for each of these roles. I own the writing of the job descriptions & the creation of the hiring process. Ultimately, I hire and manage each of these roles. I’ve looked at more resumes than I can count- and thus have a strong perspective of what sticks out.
2 - Tailoring Your Resume
2.1 BowTied_Raptor
I spend about 5 seconds (max) looking at your resume. Here’s what I look for:
General Competence: I look for keywords associated with Machine Learning, and Data Science
Technical Skills: R/Python, SQL
Preference given for industry knowledge: If I’m looking to hire a MLE for a property analysis role, if you can highlight some relevant work experience. Then, that resume gets my preference
If you are looking for the absolute specifics, then you can read this post on resume building.
If you fill your resume up with fluff, and it doesn’t answer any of the answers that I have above in about 5 seconds. Your resume goes to the trash by default.
2.2 BowTiedWhiteblt
What’s most important for you to know about the resume is, as a hiring manager, I rarely spend more than 5 minutes looking over it on my first pass. That first pass is me to gauge “Does this person match the profile of who I think can do this job”. What does that mean in practice? I want to see if you’ve worked with our technology stack. I want to see if you worked in a company/industry similar to ours. (If I recognize the company and have a good impression of it - it goes a long way).
With that in mind, what you need to highlight are:
Technical skills you have
Examples of those skills are being put to use. Ideally, in the context of professional projects that could be something you are asked to do on my team
Any industry-specific experience that could give you a leg up
KPIs associated with the output of your effort I want to see if you’ve executed the type of work you’d be expected to deliver on the day-to-day of the role.
If I’m interested, I may click over to the candidate's LinkedIn to see if I can get any other context not listed on the resume. The whole purpose of the resume is to communicate to the hiring manager if you are the correct profile of someone who can get the job done. The first minute of looking at your resume is a filter to see if “Fit the profile” of the open role. From there, it’s on you to make that experience sing.
3 - Demonstrating Work Experience
3.1 BowTied_Raptor
You should showcase 3 things within your bullet points.
When writing bullet points for your work experience, make sure you address these:
Data skill
Technical skill
Company Impact
My preferred way is to tell everyone to use a keyword for the data skill, then showcase how your technical skill led to some serious impact for the company.
Here’s an example:
Machine Learning: Used XGBoost and pairwise ranking to make the Analyst Revisions Model better. This resulted in lower volatility, and also lower operating costs.
Here are the 3 key points that the above bullet point highlights.
Data Skill: Machine Learning
Technical Skill: XGBoost
Company Impact: Reduced turnover costs
3.2 BowTiedWhiteblt
Accurately describing your experience in a concise way is what will get a hiring manager or recruiter excited for an interview. It’s what can give you an “Unfair Advantage” against the competition.
There’s a simple formula I like when reading over resumes
For X INDUSTRY, utilized Y PROCESS utilizing TECHNICAL LANGUAGE/TOOL to drive Z QUANTIFIABLE CHANGE
I want to know where you were, what you did, how you did it, and what are the results.
In practice, this could be: “Built a churn dashboard in tableau to categorize users approaching their renewal date, resulting in a reduction of churn of 5% after adoption”
4 - ATS Optimization
4.1 BowTied_Raptor
The ATS that we have here looks for 1 item within each category:
Quant Modelling: Barra, Bloomberg, blpapi, factors, etc…
Analytic (Technical Skills): R, Python, dashboard,
SQL
Other tools: Docker, Apache, Network, ETL
Once it’s done, it’ll then re-rank the resumes for us, and we go ahead, and get HR to call the top 20 candidates.
4.2 BowTiedWhiteblt
The main keywords you want to tag are:
Technical tools
Scripting languages
Statistical processes
Common business applications of analytics
Infrastructural activities are commonly used in analytics.
For me, I have my recruiters look out for:
SQL
Data visualzation tools
ETL tools
Python or R
Statistical methodologies common in Data Science Work
Common analytics use cases in my industry
The easiest way to optimize for this is to look at job descriptions for desirable jobs. You then can reverse engineer them incorporating your experience. The output of that effort will be an ATS-optimized resume that can pass all screening.
5 - How Your Resume Translates To The Interview
5.1 BowTied_Raptor
Once the ATS has filtered your resume out. Usually, we’ll get a stack of 200, which then gets shrunk down to the top 15. Everyone within this pile will get an interview from HR.
HR will ask you 3 questions:
Describe your experience with *R/Python, SQL* technical skills
Describe your experience with Factor (Quant specific) risk modelling
Describe your experience working with key stakeholders
These questions give us a simple guide on how well you can perform, once hired here. At this point, we’ll have you do a technical interview to prove your skills. Once you pass this technical interview, you’ve pretty much proved you can do the job, just don’t fk up the final interview with the team lead.
5.2 BowTiedWhiteblt
In short, your resume means nothing if you cannot deliver the goods in the interview process. An optimized resume is but a box you must check before being considered for a role. It’s an important box, however, as it directly feeds into the interview process. Before every interview, whoever is conducting will quickly read through the bullet points of your CV. They will hone in on the experience or skills that are relevant to the expertise of that interviewer.
In the churn example from before, a business stakeholder would ask for details about the contract structure of the clients. A data engineer would ask about 3rd part ETL tools you’ve worked with and your experience of data wrangling in general. The goal of a resume is to have enough “Meat on the Bone” that any possible interviewer has something relevant they want to ask about.
When they ask you the question, their goal is twofold. They want to:
Confirm that the experience you listed is indeed real, and that you executed such work
See how you think and approach a project that you may be asked to execute on the job
Think of your resume as a “Menu” of possible work experiences that the interviewer can order discussions. Done right, you have something to eat for everybody.