Our client is an innovative spin-off from Universitat de Barcelona, dedicated to transforming the food packaging industry. They're on a mission to reduce food waste with our smart labeling solution, integrating chemistry, computer vision, and AI. Here's your chance to lead vital data initiatives that drive growth and efficiency, impacting the future of smart packaging.

We are looking for a Data Scientist.

Requeriments:

Data Science: 2+ years experience
Python: +2 years experience with significant expertise in its key libraries (numpy,scikit-learn, xarray, matplotlib, etc.).
Languages: Fluent written and spoken English proficiency for accurate report writing and effective participation and presentation in meetings.
Education: Bachelor's/Master's degree in Computer Science, Mathematics, Engineering, orrelated field. A portfolio showcasing relevant projects is a plus.
Computer Vision: Solid experience with OpenCV, TensorFlow, Keras, PyTorch or similar, demonstrating the ability to bring vision-based projects to life.
Code Excellence: A commitment to clean, efficient, and well-documented code and robust testing practices (from unit tests with pytest to simulating complex scenarios with mockups).
Collaboration Tools: Proficiency in Git (including advanced operations such as merge branch, and conflict resolution) and familiarity with Linux.

They offer:

Indefinite contract: 35-40k€ gross/year in function of proven experience.
Full-time 37.5 hour workweek with flexible hours.
Hybrid working model (2-3 days of remote work) with access to a coworking space at StartUB!
25 days of annual leave. Day-off on your birthday.
Training and development opportunities, be proactive and ask for what you need.
Entrepreneurial environment and great team atmosphere with the opportunity to create something big as a team from scratch and to lead your own work while learning from and being guided by more experienced mentors.
Immediate incorporation.

Pluses:

QR Code technology (QR code generation and decoding with tools like qrdecode in Python).
Production Readiness: Skills in deploying AI/ML/DL models to production, emphasizing stability and performance.
Containerization & Cloud: Basic knowledge of Docker and Cloud services like GCP or AWS.

Soft skills:

Team player. Ability to collaborate effectively as part of a multidisciplinary team.
Initiative. Proactive in taking action and a creative thinker.
A high level of responsibility and organizational skills. Ability to prioritize tasks and efficiently manage time to meet deadlines.
Leadership. Ability to guide and motivate a team, make decisions, and assume responsibilities.
Critical Thinking. Ability to analyze information objectively and make decisions based on data and evidence.
Excellent communication with both technical and non-technical stakeholders.
Strong attitude for proactive problem-solving. Ability to adapt to changing environments and quickly learn new technologies and methodologies.
Curiosity & Learning: a commitment to keeping up-to-date with emerging technologies.

About the role

You will play a crucial role in shaping the direction of their solution and of collaborative projects with customers. Your key duties and responsibilities will include:

Lead the design, development, and implementation of computer vision models to address specific customer problems and enhance their products and services.
Conceptualize and develop solutions, leveraging available technologies within their company to meet the specific needs of client projects. This involves a deep understanding of their technological stack and the unique objectives and challenges of each client, ensuring proposed solutions are feasible, efficient, and scalable.
Analyze and Optimize: Build data processing pipelines and analyze vast datasets to improve their solutions continuously.
Collaborate with interdisciplinary teams to integrate color correction and computer vision solutions into the product development lifecycle.
Stay updated on the latest advances in computer vision and data science, evaluating and incorporating new technologies and methodologies as beneficial.
Manage and mentor other members of the data team, fostering a learning environment and continuous growth.
Present findings and recommendations clearly and accurately.

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