Ofertes d'ocupació de Científic/a de Dades a Barcelona

• Flexibilitat horàriaSi
• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada25 de març

Teletreball Python TSQL Azure Hadoop AWS R Cloud Coumputing Spark Big Data Machine Learning Power BI Tableau

Sobre Nosotros

En ORBIDI, somos pioneros en el uso de tecnología avanzada, inteligencia artificial y modelos predictivos para propulsar el crecimiento de las pequeñas y medianas empresas (PYMEs). Nuestra pasión por la innovación y el marketing nos motiva a buscar soluciones creativas que permitan a las empresas no solo competir, sino destacar en el mercado actual. Creemos firmemente en el poder de la digitalización y cómo esta puede transformar los negocios para mejor. Buscamos talentos creativos y estratégicos que compartan nuestra visión y deseo de hacer una diferencia tangible en el mundo empresarial.

El Rol

Buscamos un Data Scientist talentoso con la capacidad de analizar grandes conjuntos de datos para extraer insights valiosos y desarrollar modelos predictivos que respalden los objetivos comerciales. El candidato ideal debe tener experiencia en el diseño, implementación y optimización de modelos de machine learning para problemas de pronóstico, clasificación o clustering. Además, se espera que el candidato sea competente en el procesamiento y limpieza de datos, así como en la creación de visualizaciones claras y reportes que comuniquen hallazgos a las partes interesadas. Se valorará la capacidad de trabajar en equipos multidisciplinarios para entender las necesidades de datos y presentar recomendaciones basadas en análisis rigurosos. El conocimiento de herramientas de big data y técnicas estadísticas avanzadas es esencial, así como el compromiso con el aprendizaje continuo en el campo de la ciencia de datos.

¿Cuál será tu misión?

• Analizar grandes conjuntos de datos para extraer insights accionables, identificar tendencias y desarrollar modelos predictivos que respalden los objetivos comerciales.
• Diseñar, implementar y optimizar modelos de machine learning para problemas de pronóstico, clasificación o agrupamiento.
• Procesar, limpiar y verificar la integridad de los datos utilizados para el análisis; identificar patrones, tendencias y relaciones en los datos.
• Crear visualizaciones de datos claras y fáciles de entender, así como informes para comunicar insights y hallazgos a las partes interesadas.
• Trabajar en estrecha colaboración con equipos multidisciplinarios (ingeniería, producto, marketing, etc.) para entender las necesidades de datos, desarrollar soluciones y presentar recomendaciones.
• Diseñar y analizar pruebas A/B para medir la efectividad de los cambios y mejoras en productos o procesos.
• Utilizar herramientas de big data (Hadoop, Spark, etc.) y plataformas en la nube (AWS, GCP, Azure) para procesar y analizar datos a gran escala.
• Aplicar técnicas estadísticas avanzadas como análisis de regresión, pruebas de hipótesis y análisis de series temporales.
• Ayudar en el desarrollo de estrategias de datos y políticas de gobernanza de datos para la organización.
• Mantenerse al día con las últimas herramientas, técnicas y mejores prácticas de ciencia de datos; participar en el aprendizaje continuo y en el desarrollo profesional.
  
  

• Título universitario (se prefiere maestría o doctorado) en Ciencia de Datos, Estadística, Informática, Matemáticas o un campo relacionado.
• Más de 2 años de experiencia en ciencia de datos, machine learning o un campo relacionado.
• Dominio de lenguajes de programación como Python o R.
• Sólido conocimiento de frameworks de machine learning (TensorFlow, PyTorch, Scikit-learn, etc.).
• Experiencia con bibliotecas de manipulación de datos (Pandas, NumPy).
• Habilidades en SQL para consultar bases de datos.
• Familiaridad con herramientas de visualización de datos (Tableau, Power BI o matplotlib).
• Experiencia con plataformas de computación en la nube (AWS, GCP, Azure).
• Fuerte base en estadísticas, probabilidad y técnicas de optimización matemática.
• Capacidad para explicar conceptos técnicos complejos a partes interesadas no técnicas de manera clara y concisa.
• Capacidad demostrada para resolver problemas complejos y pensar de manera crítica y creativa.
  
  

• 🕑Flexibilidad horaria
• 💎Oficinas modernas en Sant Cugat, frente a la estación de FGC de Mirasol.
• 💰Salario competitivo y contrato indefinido
• 🤑Bonus basado en el cumplimiento de objetivos de tu equipo
• 🌴23 días laborales de vacaciones + 🎂día de cumpleaños
• 🏠Formato Híbrido con teletrabajo 2 días a la semana.
• 😍Jornada intensiva todos los viernes del año.
• 📅Agosto flexible
• 🥳Actividades de teambuilding y celebraciones y off-sites
• 🤩Referral Program
• 🤸🏻♀️Descuento en gimnasio
• 🍎Fruta en oficina
  
  

• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada23 de març

Python MATLAB Machine Learning

Direct message the job poster from ABLE Human Motion

Co-founder/CEO @ ABLE Human Motion: democratizing exoskeleton technologyLocation: Barcelona, Spain

About Us: We are a pioneering start-up that creates lightweight, quick to adjust, and accessible robotic exoskeletons for rehabilitation.

Our mission is to democratize access to this technology, improving the rehabilitation, health and quality of life of millions of people with mobility impairments.

Position Overview: We are seeking a highly motivated Data Scientist with a PhD degree to join our outstanding team.

You will play a key role in driving our AI initiatives, analyzing data, and developing models to optimize the performance and user experience of our robotic exoskeletons.

This is an exceptional opportunity to contribute to cutting-edge research and directly impact the lives of patients worldwide.

Key Responsibilities: Data Analysis & Pattern Recognition: Analyze exoskeleton usage data to identify correlations between robot parameters and user performance.

Use machine learning techniques to determine trends among expert users versus those facing more difficulties when walking with the exoskeleton.Adaptive Parameter Modeling: Develop AI models to automatically adjust exoskeleton control parameters, promoting independent patient use.

The goal is to enable users to operate the device with minimal assistance from the therapist and only with crutches.Step Detection & Gait Automation: Create predictive models to identify when the exoskeleton will make a misstep, and automatically change the appropriate parameters to avoid it.

Begin by designing a universal model and progressively refine it into patient-specific models using individualized data.Requirements: PhD degree in Machine Learning, Artificial Intelligence, or related.Demonstrated expertise in applying Machine Learning to robotic applications.Have a valid permit to work in the European Union.Proficiency in programming languages such as Python or MATLAB, and familiarity with frameworks like TensorFlow, Google Colab or PyTorch.Proficiency in written and oral English.How to Apply? Send an email to ****** attaching your CV with the subject "Data Scientist".

Seniority levelEntry level

Employment typeFull-time

Job functionEngineering and Information Technology

IndustriesMedical Equipment Manufacturing

#J-18808-Ljbffr

• Flexibilitat horàriaSi
• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada17 de març

Python Agile TSQL Azure Cloud Coumputing AWS Machine Learning Office

Wallapop is a Barcelona-based scale-up driven by the purpose of empowering people to embrace a more conscious and human way of consumption. We believe in a world where a collaborative economy is mainstream. This is what drives us.

Wallapop operates in Spain, Italy, and Portugal, offering a catalog of several hundreds of millions of products and services. Powered by technical innovation and continuous improvement, we bring together the scale & trust of classifieds with the marketplace´s convenience & reach. Our mission is to enable a connected trade ecosystem, making 2nd-hand the norm through smart use of technology.

Backed by top investors such as Accel, Insight Partners & Naver Corp we bring our total valuation to 690 million EUR and are embarking on our international journey with the aim to become the world´s best unique goods trading platform.

The Challenge

The Wallapop platform generates tons of data and, with a mature data infrastructure already in place, the area of Data Science and Machine Learning is gaining momentum. The team is experiencing significant growth and, with many initiatives down the road, the opportunities are endless.

As a Data Scientist in the Wallapop you will be working on the Data Science and Machine Learning initiatives aimed at improving the whole marketplace dynamics. This will include topics such as improving models that power users´ main interaction point: Search. You will also look into various models that will help users discover new items through ranked Recommendations, Similar Items, and more.

You will work closely with other Data Scientists, Product Managers, Engineers, UX Researchers, and Analysts to understand the product requirements and explore possible data and ML solutions. You will own the whole product lifecycle, from gathering the data needed to prototyping, building, evaluating, and iterating end-to-end solutions, all within Wallapop´s Data and ML Platforms.

Additionally, you will have the opportunity to work on internal research projects, exploring new technologies and building PoCs that could ultimately become data products or insights, and be valuable for Wallapop.

You will be part of a growing Data Science team within the Data & Analytics department (30+).

What You Will Do
- Collect, clean, and analyze large datasets from diverse sources, including user behavior, transactions, and market trends.
- Develop and implement machine learning models to solve business problems, such as personalized recommendations, fraud detection, and pricing optimization.
- Work with multidisciplinary Product teams to identify opportunities and gather requirements (both in terms of product and tech).
- Own initiatives from start to deployment: ideation, data processing (ETL), modeling, testing, deployment, monitoring and iteration (w/ help from Engineering partners)
- Proactively suggest, research and prototype new ideas for data and ML solutions.
- Communicate complex data insights to both technical and non-technical audiences, including stakeholders involved in marketplace operations.

What We´re Looking For
- Bachelor or MsC degree in engineering, mathematics, statistics, physics, or another quantitative field.
- Strong coding skills (Python is a must, but other languages are also valued), capable of building robust data and ML software.
- Experience building complex data products and ML solutions to real-life problems in a production-oriented environment, identifying the right techniques to solve the problem at hand.
- Experience with common libraries and frameworks such as Pandas, Numpy, Scikit-learn, TensorFlow, Keras, PyTorch.
- Advanced in SQL, capable of getting the data required from the appropriate sources, and building and maintaining data pipelines if needed (experience in tools such as Airflow or DBT would be a plus).
- Excellent communication and presentation skills, with the ability to explain data insights to business stakeholders in the context of marketplace dynamics.

What Would Be A Plus
- Experience working with Search & Ranking models in production environments
- Experience working within an eCommerce or Marketplace platform, or in a product-tech company.
- Experience working within the Logistics, Trust & Safety or Customer Service domains.
- Experience working within the AWS cloud (Redshift, S3, Lambda), and with cloud MLaaS solutions such as Amazon SageMaker (preferably), but also Google Vertex AI, Microsoft Azure ML, and other MLOps tools (MLFlow, Flyte, Feast, Kubeflow, etc).

Do note that all our jobs are Barcelona based. We follow a hybrid model where flexibility rules. We commit to a minimum of 6 days per month in the office. Each team self-organizes to decide on cadence and in-person/remote rituals.

Wallapop is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees as we want Wallapop to be a place for everyone.

We sponsor visa processes for international candidates when applicable and provide legal & admin support along the process combined with a competitive relocation package.

Additionally to the opportunity to contribute to an agile product set up and work together towards achieving our meaningful mission, we offer the following Perks & Benefits:
- Competitive phantom shares package for all employees
- Generous individual learning budget of 2k per year
- Group and individual English, Catalan & Spanish lessons as part of our working day
- Private Health Insurance with Alan
- Flexible working hours + intensive Fridays
- Flexible remuneration to deduct from gross salary (kindergarten/food/transport check)
- Gym & Wellness plan, including physiotherapist in the office
- Generous referral Program & Charity Donation
- Bonus for weddings & newborns
- Wallapop Renta (Tax income support)
- Monthly plan for free shipping, bumps & home-pick-up on our services
- Work anniversary Gifts and Birthday Surprises
- Contribution towards your WIFI in your monthly payroll
- One-off payment based on compensation package to go towards setting up your home office
- Relocation package (monetary support and legal advice) and visa sponsorship, if applicable
- 26 holidays per year
- TOP hardware of your choice (latest Apple or Windows)

What does the hiring process for this position look like? **Please, note that all interviews take place remotely over hangouts.
**

Intro Call - run by talent acquisition, focus on providing more information about the role and the company as well as going over your experience, motivation, and expectations. This usually takes 45-60 minutes.

Task - you will be assigned a task to submit within 5 up to 7 days where you will be able to showcase your expertise and technical skills required for the role.

Expertise Interview - run by the hiring team, focus on the required core skills and the ability to deliver in a given context. This usually takes 60-90 minutes.

Stakeholder Interview - run by relevant stakeholders reflecting the reality of the context of the role, focus on the ability to collaborate & deliver in a cross-functional set-up. This usually takes 60 minutes.

Culture-Add Interview - run by culture interviewers, focus on adherence to Wallapop´s purpose and business proposition. This usually takes 60 minutes.

Offer - should you be the right candidate, your offer will be discussed over a call with talent acquisition and will then be confirmed in writing.