Decoding the Consultant Life: Real stories from real consultants – Miska & Saka
Miska, a Data Scientist, discusses working with our customer, Saka, to optimize their inventory logistics.
I am Perttu Pakkanen, and my interest as Codento’s talent acquisition lead is to better articulate why consulting at Codento could be a great career choice.
When potential customers ponder whether they should use our services, they usually like to see some reference cases. Why wouldn’t our potential employees think the same?
So, I had a chat with our Data Scientist, Miska. He has been working with our customer Saka for optimizing their inventory logistics. Saka is a used car retail chain with over 30 locations across Finland, with thousands of cars in their inventory at any given time. So, optimizing this puzzle had a clear business case.
I asked Miska to sit down with me in our office’s meeting room on a November Tuesday morning. The weather outside was just as you’d expect November weather to be in Finland, but it didn’t slow us down.
Here we go:
What kind of solution have you built?
“We developed an end-to-end data science solution in Google Cloud to improve car logistics.
As part of the project, we also had to define what constitutes good car placement and logistics across the entire network of dealerships in Finland, and what metrics we would start optimizing.
The work involved modeling predictive factors and features based on multiple data sources the client has been collecting in their data warehouse in Google Cloud.
I liked that the work was structured according to the data science process: I got to delve into the database and discuss with the customer stakeholders, and only then start building and putting the solution to production. Enough time was allocated for us to carefully consider the background data.
Now, the ongoing work involves continuously developing the solution and implementing improvements in good collaboration.”
What kind of tasks have you done in the project?
”The project was a classic data science case, and the model we followed adhered quite closely to the standard data science project steps. I got to execute the process meticulously in the correct order, just as a data scientist should.
In addition to the technical work, I was heavily involved in project management and client communication.
I also played a strong role in the project’s sales phase, so I got to shape how the project is planned and executed from the beginning.
Currently, we are engaged in iterative model improvement.
Overall, I was involved in the project from end to end.”
What has been the most interesting thing you have done working for the customer?
”One of the most rewarding aspects was the extensive data exploration phase. I had access to a large data warehouse, which allowed me to build various features.
This gave me the opportunity to work with a truly massive amount of data and focus on feature engineering, leading to the development of a highly tailored solution.
It was not always straightforward to capture the most meaningful signals from the data, which was an interesting challenge.”
What has been the most difficult part?
“One of the challenges we encountered was the intrinsically random nature of the problem. Aggregating a holistic view from the intrinsically random process of selling an individual car.
I had the opportunity to manage the entire project broadly, which allowed me to learn and be flexible in my approach. This was a challenge and a learning experience.
This was also one of the client’s first larger AI application cases, meaning the technology and operating environment were still taking shape, particularly in establishing a smooth data flow.
Everything went well with good collaboration, though!”
What have you learned?
“This was a fully Google Cloud project, which allowed me to effectively utilize the skills I learned from the certifications in a production environment.
I gained practical experience with Vertex AI, including model registries, pipelines and other related components.
So, lots of Google Cloud learnings!”
That’s a lot of learning! Any last words to wrap things up?
“From a Data Scientist’s perspective, this project was executed correctly right from the start, and in a modern cloud native approach on Google Cloud.”
Thanks, Miska!
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Being part of pioneering projects like this allows for both personal and professional development. I strongly feel that at Codento, you can engage in work that is not only challenging but also highly impactful in many industries.
Read more about us from our career site and see if there are any suitable opportunities for you, and connect with us on our recruitment system!
About the interviewee:
Miska is a data scientist who takes ownership of the full data science lifecycle, bridging the gap between high-level business strategy and complex technical execution. He ensures that challenging projects transform from initial client concepts into robust, production-ready solutions.
About the interviewer:
Perttu Pakkanen is responsible for talent acquisition at Codento. Perttu wants to make sure that the employees enjoy themselves at Codento because it makes his job much easier.
