Junior Data Scientist with English (Recent Graduate Opportunity)

Universia; Barcelona; Presencial; EUR 20.000 - 35.000; Jornada completa

Descripción de la vacante

A fast-growing technology startup seeks recent graduates for a Data Science Intern role in Barcelona. As part of a vibrant Data Tech-Hub, you'll support data analysis and machine learning projects, learning from experienced professionals while contributing to high-impact ad-tech solutions. This opportunity promises growth and the chance to innovate in a dynamic environment.

Formación

• Strong analytical skills and ability to derive insights from datasets.
• Solid understanding of statistical modeling and machine learning fundamentals.
• Excellent communication and collaboration skills.

Responsabilidades

• Assist in analyzing data to identify trends and actionable insights.
• Participate in design and development of data science solutions.
• Collaborate with teams to enhance advertising effectiveness.

Conocimientos

Analytical skills

Collaboration

Communication

Educación

Bachelor's or Master's in Computer Science

Bachelor's or Master's in Data Science

Bachelor's or Master's in Statistics

Bachelor's or Master's in Mathematics

Herramientas

Python

SQL

Pandas

AWS

PySpark

DNN libraries

Descripción del empleo

Are you a recent graduate, passionate about challenges, and excited about working with cutting-edge technologies?

Are you motivated by transforming data into strategic knowledge and generating real impact?

Would you like to be part of a dynamic, international environment full of opportunities?

Our client, a fast-growing technology startup, is on a mission to accelerate the global success of mobile applications. Backed by a strong client portfolio of top-tier developers and publishers, the company operates from three strategic hubs: Spain, Poland, and the United States. As they continue to scale, they are now expanding their team in Barcelona and seeking motivated recent graduates eager to kick-start their careers and contribute to an ambitious, high-impact project.

Join a vibrant Data Tech-Hub where you can grow and learn from a passionate team of Data Scientists, Data Analysts, and ML/Data Engineers is ready to innovate and inspire!

Main Responsabilities

• Assist in analyzing data to identify trends, patterns, and contribute to actionable insights under the guidance of senior team members.
• Participate in the design and development of data science solutions
• Contribute to various stages from initial analysis and model development to deployment, with a focus on optimizing for performance and scalability within ad targeting, bid strategies, and campaign performance analysis.
• Collaborate with technical and business teams to understand requirements and contribute to data-driven solutions and insights, particularly focusing on enhancing advertising effectiveness and ROI, while learning from experienced colleagues.
• Assist in maintaining and optimizing existing data processing pipelines and machine learning models, with a focus on applications within the ad-tech ecosystem
• Contribute to the exploration and evaluation of new data science techniques and technologies relevant to AdTech.
  
  

Core Skills/Experience

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
• Strong analytical skills with the ability to learn how to derive insights from datasets.
• Solid understanding of statistical modeling and machine learning fundamentals.
• Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
• Tech Stack (Exposure and Willingness to Learn):
• Proficient in Python and SQL.
• Familiarity with data manipulation frameworks such as Pandas.
• Exposure to big data processing concepts (e.g., PySpark) is a plus.
• Basic understanding of ETL processes and tools (e.g., concepts similar to Dagster).
• Basic understanding of OLAP database concepts (e.g., concepts similar to Druid).
• Familiarity with cloud services (e.g., AWS) at a conceptual level.
• Exposure to DNN model training libraries and frameworks (e.g., PyTorch, TensorFlow, Hydra, Comet) through coursework or projects.
• Knowledge of Databricks (even through academic projects) is a plus.