Crunchbase

-Conducting analytics and designing product experiments for the Trial Experience team to improve key trial metrics and convert users. Interpreted results and provided recommendations for stakeholders and leadership. (A/B & Pre/Post Tests, Power Analysis)
-Optimized 30+ slow queries and dashboards and improved stakeholders' experience by identifying which queries would benefit from being moved to an upgraded data warehouse 
- Researched and summarized dashboard best practices that were implemented across the team

Senior Data Analyst

Big Data Energy Analytics⚡️

I offer brand partnerships on LinkedIn, Instagram, TikTok, the Big Data Energy newsletter, and at virtual and in-person events and conferences. I also create courses on data analytics & SQL!

Founder

LinkedIn

Planning a curriculum and teaching courses on Analytics through LinkedIn Learning’s platform. 

- Preparing to Get a Job in Data Analytics - released Feb 2023
- Solving Real-World Data Problems in SQL -released Sep 2023

LinkedIn Learning Instructor

Freddie Mac

Single Family, Credit Innovation and Analytics
Tech Stack: SQL, SAS, Python, Tableau

-Conduct research and analytics to support borrower assessment rules for Freddie's Loan Product Advisor Asset Income Modeler (AIM) product which automates the manual process of assessing a borrower's asset and income.

Senior Risk Analyst

Technology Association of Georgia

Volunteer through TAG Data Science and Analytics for Good Initiative and serve on the board. 

As a team, we cleaned, transformed, and engineered a very messy dataset from a non-profit organization. Then we developed a k-means cluster algorithm to identify significant clusters from their donor base. 

I was solely responsible for developing personas for each cluster based on their historical behavior, demographics, and characteristics and then telling a story with each persona in a way where the non-profit could understand their donors and take action to increase donations.

Data Scientist

FormFree®

Tech Stack: SQL, Power BI, Excel, Python, HubSpot

•	Oversee all BI operations by delegating tasks to team, communicating expectations, and providing feedback.
•	Identified and reconciled $100Ks in billing errors; optimized and redesigned client onboarding process to ensure accurate database logging and billing. 
•	Engineered billing tables and views in the database to improve data collection for the billing system.

Data Analytics Manager

• Provide weekly insights and updates on both a Sales and company-wide call in order to ignite strategic action.
• Provided essential data and compelling visuals on short notice over a 3-month period working with potential investors.
• Run and modify monthly billing queries as needed for all clients and partners for the Finance department. 
• Design metrics, reports, and dashboards (in SQL and Power BI) relating to volumes, revenue, and software system performance for teammates, partners, and clients.

•	Implemented robot process automation (RPA) software to send monthly client reports which reduced the monthly task time from days to just minutes.
•	Designed a monthly client report in Power BI featuring useful metrics and visualizations to track performance and integrated the report into the RPA software.
•	Construct queries in SQL and Power BI to filter, transform, and visualize desired data to be delivered internally and externally.
•	Report on important metrics, craft dashboards, and query reports that provide meaningful insights into clients, prospects, and the company as a whole.
•	Update and import data into Power BI from various sources (database, excel, Box, HubSpot), manage the data model (ERD) to ensure proper data relationships using primary/foreign keys, and transform the data for analysis.

Data Analyst

•	Constructed queries in SQL to manipulate, filter, and extract desired data and delivered to team members. 
•	Created queries, measures, and visualizations in PowerBI in order to clean, transform, and visualize data.
•	Reported on important metrics and crafted dashboards for several departments, many which were used in the company end-of-year meeting.
•	Queryed reports for clients and integrations and set alerts for their corresponding FormFree representative.
•	Assisted the Business Intelligence Manager in office with various analytic projects while also managing several individual projects remotely with minimal supervision.

Data Analyst Intern 

Caterpillar Inc.

Completed a capstone project for my Master's program. Worked on a team with Caterpillar executives on a scalable analytics solution for their supply chain.

Analytics Consultant

The University of Georgia

•	Cleaning and transforming messy and unorganized data sets, collecting data, and improving data collection and entry for leaders at Archway Partnership and in Moultrie City.

Graduate Assistant

Berry College

I worked on a data project to predict and improve enrollment at Berry College. I turned a ginormous, messy dataset of 113,000 observations into a usable asset for the Enrollment Management Office, and I learned the importance of data cleaning and transformation. I developed a passion for data, and this job led me to pursue a job in analytics.

Data Scientist, Predictive Analytics in Enrollment Management

I led an ESL classroom through Berry's ESL program. I was responsible for creating lesson plans, assisting students, and making a connection with the local Hispanic community. I helped them strive to do their best and improve their English skills one day at a time.

English Second Language Teacher, Lead Educator

I tutored students in Berry's academic success center. I was responsible for assisting them with their questions and homework and maintaining a professional environment in the tutoring center.

Calculus and Spanish Tutor, Presentation Coordinator, Event Planning

Fundación Progreso Guanacaste

I served as an intern teaching English in a local school in Santa Cruz, Costa Rica for 2 months. I created my own lesson plans, led classrooms, and became an American friend to the children I taught. I was also in charge of planning a school-wide English spelling bee and several other events. During my trip, my Spanish skills skyrocketed, and I became a very independent and responsible young adult. This trip taught me to be confident with my skills and also to respect other cultures that are different than my own.

Assistant English Teacher, Educator, Event Planner

Sr. Data Analyst @ Crunchbase | LinkedIn [in]structor | Data & SQL Tips

I'm a senior data analyst in who specializes in product analytics in SaaS startups. I get really excited about AB testing, SQL, and thinking from the user's point of view! I'm also an Instructor with LinkedIn Learning-- check out my 2 data courses with 50K learners! I really enjoy teaching others and providing approachable learning opportunities for others. 

My side hobby is running my business, Big Data Energy Analytics⚡️ which supports my social media content (on LinkedIn, Instagram, & TikTok @JessRamosData), my newsletter (Big Data Energy⚡️), brand partnerships, and speaking collaborations. 

I strive to combat stereotypes in the data and tech industry by showing women that they can be their full confident selves while pursuing a data career. And I'm gonna do it while wearing pink and being loud.

I'm hiring a social media intern for my company, and I did something crazy: I sent all the candidates the interview questions ahead of time!

Why? 

I wanted them to be their most confident selves and well-prepared for the interview. My goal isn't to stump them and trick them, my goal is to see how they think about and talk about some of my questions with a little bit of background info and time to think about it. 

If I ask them questions on the fly, I'm only seeing who's the best interviewer-- aka best bullshitter. And that doesn't do me any good when I want to see who can best apply their skills to my business problems. 

Well-prepared candidates interview better. Preparing candidates builds trust and shows them that you're willing to meet them halfway. Plus, an unexpected benefit is that I've been able to see who spent a little time (and a lot of time!) preparing and taking the interview seriously, and who didn't and just wanted to get lucky. 

All companies should send candidates interview questions beforehand.

Jess Ramos, MSBA

I'm not usually a big fan of cheat sheet clickbait because what are you actually supposed to do with them?! Read them every night before bed?🤣

In the age of not only Google but ChatGPT, we have all this code and defined functions at our fingertips, so who really needs a cheat sheet nowadays to reference?

BUT as I'm coming up on my 6 year mark working in data, I decided that it may be useful for my community to share my top-used SQL skills so people know where to focus their time when learning. 

Should you learn all of the niche functions and be ready for every situation possible?! Absolutely not! You can Google and ChatGPT them as you go when the time comes when you need those. 

But you should learn the bread and butter of SQL because these are the skills you'll use all the time on the job. 

Here's a summary of the most important SQL skills-- in my humble opinion 😉

At my first job as a Data Analyst, I made a very junior mistake. I made everything as technical as possible because I thought having complicated calculations and complex visuals would mean better insights. I mean, it makes sense right? More is better!

As I grew in responsibility, I quickly learned that one of the most important roles of a Data Analyst was the ability to communicate technical issues to non-technical stakeholders. 

For some non-technical stakeholders, using the SUM() function in excel is enough to make them panic or make their eyes gloss over. 

So why did I think they wanted to know the ins and outs of my process and calculations? 

When working with stakeholders, it’s best to shield them from everything you possibly can. They don’t need to see the mess under the hood, and they certainly don’t need to see complex calculations and visuals. 

Always tell your stakeholders important details such as:
✔️Assumptions
✔️Filters
✔️Time period

Stick with simple visuals:
📊Bar charts
📈Line Graphs
🗒Tables

And I bet your relationship with them will change and grow in trust. 

As a Data Analyst, you also work as a data translator. A data storyteller. A data ally. 

Complex != Better

Things Junior Data Analysts Google: 

- How to build ML models from scratch
- How to fine tune LLMs
- Using deep learning to derive insights
- Deploying models to production
- How to design AB tests

Things Senior Data Analysts Google: 

- How to import CSV w/ Pandas
- What is a P value
- DateDiff syntax
- Why isn't my Excel function working
- What is this error

The more experienced I get, the more I find myself Googling the simple things (and having to relearn things again) 🤣 

Things that should send data analysts straight to jail:

1. SELECT *
2. Leading commas
3. Nested Subqueries
4. No code comments
5. Writing queries on 1 line
6. Not indenting your queries
7.  Pie charts with 5+ categories
8. Using Google Sheets instead of Excel
9. Pushing view and dashboard changes straight to prod
10.  Changing a data source without checking dependencies


Getting a job in data science/analytics in 2024 isn't the same as it was 5 or 10 years ago. 

You used to be able to get a job in data if you could make a pivot table in Excel, but now the expectations have greatly raised especially in the age of AI and the rise in "become an analyst in 30 days" jank bootcamps. 

You know what I'm talking about. 

False promises, surface-level teachings, and an army of affiliate content creators advertising without disclosing and further pushing the narrative while secretly pocketing their commission for themselves.

Social media has become a weird place for data education because there's a lot of misinformation, and then people try into the field super quickly and then can't get a job because they're severely undereducated and underprepared. 

Who's at fault here?

Is it the course/bootcamp creator for selling false promises without a path to reach them? Is it the secret MLM affiliates pocketing money by pushing it? Or is it on the consumer for not doing their own research?

Some people might call me negative or even gatekeepy, but I call myself realistic and honest. It's not easy to get your first job in data (especially in THIS job market), and I'm not gonna tell people it is so I can profit off of them. 

It's that simple to be a decent human being. 

I was so scared when I quit my job in only 4 months because I thought no one would want to hire me as a quitter.

When I was interviewing, I was terrified that I’d look like a flight risk or that I didn’t know what I wanted. But the truth is that I knew EXACTLY what I wanted: a non-toxic manager, healthy work life balance, and to be able to use my PTO!

At the time, I was with a manager who micromanaged every minute of everyday and lived to see my Teams status dot remain green from 9-5 on the dot. He mocked me for my LinkedIn content claiming that he was “concerned what the company thought”— yet the company wanted to feature me on their page! The final straw was when he nitpicked every assignment I did and talked to me like I was stupid.

At only 2 months into the job, I knew it was my time to go. It was a bold move— even for me!

Taking this huge career risk took a ton of courage because it was something so against the norm that people commonly advise against. But I ended up increasing my salary and landing a much better role with a much better manager.

Taking career risks is hard, but I promise it won’t ruin your career ❤️

I’m SUPER excited to share Natalie Fisher’s FREE 3-day masterclass that’s designed to help you communicate your value, land 6-figure roles, and have successful careers long-term: https://lnkd.in/gXesPKB6

She has a methodology that she teaches that helps you see exactly how to do this so that it’s simple and most effective for your unique value. She's helped hundreds of undervalued professionals succeed at this already and she's excited to help you too.

If you’re job-seeking or looking to learn more about identifying, owning, and communicating your value, I highly recommend you put this on your calendar. This is an absolutely FREE 3 DAY series, so what do you have to lose by taking it?!

If you're going through something hard in your career, sometimes help is worth investing in!❤️

In my first real data analytics job out of school, I started at a humble data analyst salary of $71500 which was fine, but I quickly became a huge leader in the company bearing lots of responsibility. 

Not only did I have 2 people reporting to me, I also was responsible for leading several calls and making a lot of company decisions— which I knew were worth more than $71,500.

It was time for me to get a raise and a promotion, but all know these things aren’t handed out freely. So I typed up compelling 1-pager of all my accomplishments over the past year and showed how much my role had grown in scope compared to when I first started. Then I shared the market salary based on my research and asked for a compensation increase.

And guess what?!

I was rewarded with a 33% raise and a manager title— which was a huge setup for my career! Was I scared to advocate for myself? Abso-freakin-lutely! It was so tough to do that, but it made a huge impact on my career and finances at the time, and I’d even argue it’s still had an effect on my current career and finances.

If you want the raise or promotion, you HAVE to advocate for yourself even if it’s scary!

I’m so excited to share Natalie Fisher’s Free 3-day masterclass that’s designed to help you communicate your value, land 6-figure roles, and have successful careers long-term: https://lnkd.in/eufdx3nn

She has a methodology that she teaches that helps you see exactly how to do this so that it’s simple and most effective for your unique value. She's helped hundreds of undervalued professionals succeed at this already and she's excited to help you too.

If you’re job-seeking or looking to learn more about identifying, owning, and communicating your value, I highly recommend you put this on your calendar. This is an absolutely FREE 3 DAY series, so what do you have to lose by taking it?! #sponsored

I just hired my first employee, and I'm already learning a tough solorepreneur-with-a-9-to-5 lesson: you have to spend money to make money!

Spending money for me is generally easy if it's something I really want. Vacation? Prada purse? Eating out? Take my money!

But when it comes to business expenses and boring stuff, I struggle. Taxes, insurance, lawyer fees, and adult stuff is hard for me to spend on. 

And now I'm adding an intern, a video editor, and payroll software (and therapy!) to my list. It's tough to take on that expense because I know it's a lot of responsibly for something I could seemingly "do myself for free." But we all know that's not true because if I do something "for free" money-wise, I'm paying in my time. Which is most valuable to me nowadays. 

Spending money to delegate is buying my own time back. It's buying back some free time, mental health, and R&D time for my business. 

If I'm not good, BDE⚡️ isn't good. So I gotta take care of Jess first and protect my time. 

Making money requires spending money.
Making money requires spending money.
Making money requires spending money.

This is my daily mantra I have to remind myself when my monthly expenses go up.

Is there a handbook somewhere for how to be an adult and run a business? Asking for a friend.

Idk if it's just my LinkedIn feed or what, but I'm starting to see a lot more job announcement posts, and I LOVE IT!!

Is the market turning around and are more people landing jobs?! Or is it just that my LinkedIn feed has changed a bit?

I really hope the former. After a crappy 2023, we deserve a year with less layoffs and more job announcements! I'm hoping that employees can get the job market back in our favor so salaries can be high and layoffs will be low. 

I'm super optimistic about the rest of the year and can't wait to see how it ends up. Manifesting a happy data job market!!

Here are my top tips for data professionals: 

1. You should always use subqueries over CTEs when you can. CTEs take up too much space, so you might as well save space by nesting the subqueries and further integrating them into the query. More nests = better query.

2. Make sure you always put your best foot forward with analyses. Don't take the easy route and be lazy by just making a simple bar chart or line graph. You should always try to do more complex things and implement ML when possible.

3. It's always a good idea to use sequential aliases in your queries so the reader can more easily follow. I recommend a, b, c, d, e, f, g, h, and so on. It's makes your code cleaner and easier to read. 

4. I recommend using SELECT * when you can so you can get all of the columns just in case. You never want to limit the number of columns you pull because you might miss out on important data. More columns = More Good Data.

5. Don't waste time on silly processes like code reviews and testing code in staging if you're just making a small change and you feel confident that you have it right. Push that sucker straight to prod with confidence baby!!!

And the last tip I have that all data professionals should follow regardless of experience and job title is have a good APRIL FOOL'S BABY GOT U!

AI, Data Science, & Data Analytics are all some of the HOTTEST🥵🔥🌶️ jobs nowadays, but there’s an OVERWHELMING number of courses out there, so it can be really hard to choose the right courses to take that will advance your career. 

At the end of the day, if you’re learning something new AND enjoying it, it’s pretty hard to go wrong...

Here are some of the top things I look for when choosing a good course:

⚡️Skills: Ensure the course teaches up-to-date skills aligned with industry trends such as AI & ML.
⚡️Tools: Opt for courses utilizing tools commonly used in businesses and in high demand in the job market.
⚡️Business Application: Choose a course that not only teaches skills and tools but also relates them back to real-world business scenarios.

Since AI is SUCH a hot topic right now, I want to share a ✨FREE✨ course I found: Applying AI-powered Augmented Analytics to Business Data in SAP Analytics Cloud– which covers data science topics such as classification, regression, and time series models. 

It’s free here: ✨ https://lnkd.in/g9KUd3VX ✨ 

Augmented Analytics is an exploding topic right now because everyone from data analysts, business stakeholders, and executives wants insights at their fingertips. The future is all about quick and easy access to insights, and SAP has nailed it! And over the next two years, an anticipated 500,000 professionals with SAP skills will be sought after worldwide.

If you’re looking for some new free courses that are relevant to industry trends and software used by thousands of companies, I highly recommend you check out SAP's Learning site. 

SAP has so many great resources for those looking to upskill or even to transition into a new career and the potential for career advancement within the SAP ecosystem is boundless. Go check them out!!🤩
#sponsored


As a data analyst, there’s nothing scarier than pushing code to prod— especially if it hasn’t been reviewed by someone else.

One time, I accidentally wrote over a view in prod and almost broke a bunch of other tables and dashboards (don’t tell my coworkers!) Luckily, I had a copy of the old code (yay version control), and I was able to fix it before there was any damage or anyone noticed.

For this reason, I’m a massive fan of code reviews for data analytics teams. After all, one typo, accidental copy-and-paste, or incorrect assumption can break or cause inaccuracies downstream.

The more a team is able to work together and provide input and feedback, the more they can get rid of data inaccuracies, add new data, and fill in data holes— which overall leads to a greater impact to the organization. More collaboration = Better data!

A really cool tech startup, Sort, is solving a lot of database collaboration issues by building GitHub for databases. It’s a place where data scientists and analysts can all work together to improve data quality and add new data. Plus, the team can review each other’s work and provide feedback!

Go try out Sort for free by filtering this table for job_title = 'Data Science’ and let me know what you think!

1. Go to Sort's 2023 H1-B jobs table used for demo purposes here: https://lnkd.in/eZyq4v-u and create an account

2. Click on SQL in the top left of the table and write a SQL query that filters for job_title = 'Data Science’

3. Click Save Query

Sort currently works with Postgres and Snowflake, but they’re planning to add 30+ additional database platforms soon. Finally data analysts will have an easy way to edit the database instead of sending queries back and forth in Slack and dealing with access issues!

If you saw my post 2 weeks ago, you saw the competition for the $500 gift card. I’ll post the winner in the comments below!!💰⬇️

Happy Friday to everyone except companies that require multiple live coding interviews AND a take home assignment for mediocre-paying data roles.

I'm a PTO junkie. 

Maybe I'm about to sound old, but at this point in my life (as a very wise and seasoned lass in my 20s), time off is more important to me than money. You could offer me a job for more money with less PTO, and I'd turn it down. 

I don't like the grass to grow under my feet. Especially as a remote worker. If I can't take off, I might as well work somewhere cool like Miami right?! I just can't sit still and look at the same view outside of my window for 40 years, blink, and retire. 

My camera roll has 46,608 pictures and that's how I like it. It's full of laughs, tears, luxury views, and traveling disasters. And that's how I like it. I can't imagine growing up to be 65 and having no memories to look back on-- despite finally reaching unlimited time and money as a retiree. 

I love my unlimited PTO, and it truly makes me want to get out of bed and do good things at work. I know I have to put good in to get good out, and I don't want to do anything to screw up the privilege and luxury of being able to work wherever I want and take off whenever I want. 

PTO > Salary.

PS. This pic is from my trip to Puerto Rico last year. I can't wait for my next PTO!! Where are you headed next?

Unlimited PTO sounds good on paper but is it really a scam? 

Is it a cost saving method for companies or is it the dream work benefit?

Based on my experience, I’ll probably never work anywhere again that doesn’t offer me unlimited (or substantial) PTO. I’ve realized that my mental health, taking breaks to travel, and the flexibility to work anywhere are far more important to me than any salary or title. 

Last year, I took off almost 6 weeks. 2 were to film with LinkedIn Learning and 4 were pure vacation and mental health days.

Am I extremely privileged to be able to do this? Absolutely. But is it necessary to prevent burnout especially when working in a high-pressure tech startup environment? Ab-so-lutely!!!

Although I’ve seen unlimited PTO abused at companies and not in favor of the employees, finding a company that does it the “right way” makes it all worth it!

I once interviewed with a company that had unlimited PTO and said that on average people take off 2-3 weeks 🫣 only 2 weeks off in a tech startup?! Heck no! People get more than that in big companies nowadays…

What are your thoughts on unlimited PTO?!

Buckle up because this is the most atrocious, unhinged, and ridiculous job description I’ve ever seen. 🚩 

It’s full of red flags, nonsense, and condescending remarks. Would anyone want to work at this company or with this guy?

I’ve ended up in a job with some red flags before (although not THIS bad lol) and it’s pretty miserable to be in that kind of an environment. Candidates deserve better and they don’t deserve to be taken advantage of while the market is bad. 

Are these red flags or…

Maybe it’s actually a green flag when companies are transparent enough to put their red flags on the job description so people know about them and don’t apply 😂

What are your thoughts?

A lot of data leadership has big expectations for their teams to implement AI and ML, but they don’t give their team the resources they need to succeed. 

Most ML projects require a niche skillset of data science and lots of time and patience cleaning data. Because of this, it takes a lot of time to complete predictive projects— you have to hire the right person of expertise, onboard them, and then spend weeks (or months) preparing the data! 

If only there was another way to speed up this process and empower data analysts to pick up some of this work… 

Introducing Pecan AI🔥

Pecan AI empowers data analysts to create predictive models in only 10 minutes by using their ChatGPT-like interface to set up the business problem and data. Then using SQL notebooks, any data analyst who knows SQL can customize, train, and validate a ML model. The results are super easy to interpret and use. And the tool even works with messy data! 

Pecan AI is a MUST have for any data team who wants to unlock quality ML in a short amount of time. Sign up to talk to a product specialist today!

I promise people can tell if you use ChatGPT at inappropriate times like writing LinkedIn comments or on job application questions. 

Not only do you sound ridiculous for just regurgitating the original post or question, but you also sounds like a bland robot. 

Although AI can be really useful to generate ideas, summarize your thoughts, and increase your work efficiency, it shouldn't be a replacement for your own intelligence, creativity, and personality. If you sound like a bland robot, how will you make genuine connections on LinkedIn and stand out on a job application? 

I could tell many people who applied for my marketing internship blatantly copied and pasted from ChatGPT. Not only did they sound kind of "off" but they also just said a whole bunch of stuff without really saying anything... I knew immediately that those responses weren't from a real human. They stood out in a negative way from those who wrote thoughtful and personal answers. And THOSE are the people who got interviews. 

Maybe you think you're being sneaky and working more quickly by copying and pasting from ChatGPT, but there are a lot of instances where brainless AI copying and pasting can actually negatively impact you. 

Don't forget to use your heart and brain because after all, that's what makes us human.

Many companies see the value in ML and predictive analytics but a lot of times, they don’t have the right resources to complete the projects. Why?

ML requires a niche skill set that not every data professional has. Plus, it can take a ton of time and patience to clean and prepare real-world messy data. Leadership has goals and expectations around data science and ML, but they aren’t giving their teams a way to succeed and deliver results. 

If only there was another way to speed up this process and empower data analysts to pick up some of this work… 

Introducing Pecan AI 🔥

Pecan AI empowers data analysts to create predictive models in only 10 minutes by using their ChatGPT-like interface to set up the business problem and data. Then using SQL notebooks, any data analyst who knows SQL can customize, train, and validate a ML model. The results are super easy to interpret and use. And the tool even works with messy data! 

Pecan AI is a MUST have for any data team who wants to unlock quality ML in a short amount of time. Sign up to talk to a product specialist today!

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