Senior Data Scientist - Madrid, España - Cognizant

Cognizant

Empresa verificada

Madrid, España

hace 3 semanas

Publicado por:

Isabel García

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Descripción

What makes Cognizant a unique place to work? The combination of rapid growth and an international and innovative environment This is creating many opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.

At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world's leading companies and help them become more flexible, more innovative, and successful.

Moreover, this is your chance to be part of the success story:
we are looking for a
Senior Data Scientist to join our AIA Team.

Key Responsibilities:

At Cognizant we are looking for a Sr.

Data Scientist to lead the design, training and deployment of large-scale machine learning solutions for a wide range of clients and business areas.

Evaluate the complexity and feasibility of machine learning solutions based on the state of the art, industry standards and market trends.
Frame business needs as machine learning problems and select the evaluation metrics that are most relevant to the business.
Identify, explore and prepare largescale datasets, including structured, image and text data.
Design, build and evaluate machine learning models for a wide range of use cases, including both deep learning and classical methods.
Communicate with stakeholders and other teams.
Technical coordination and mentoring of a team of data scientists.

You will become an active member of the AIA team that works closely with other disciplines/roles and that shares experience in Digital Transformation projects in a dynamic environment with multiple roles, using last technologies according to development/test standards and corporate architecture policies.

Essential Skills:

45 years professional experience as Data Scientist.
MSc. or PhD. in Artificial Intelligence or other equivalent training.
Extensive experience designing and training machine learning models, including both classical and deep learning methods.
Extensive experience with deep learning frameworks (e.g. Pytorch, Tensorflow).
Experience dealing with largescale datasets and models.
Experience with machine learning models in production and MLOps principles and tools (e.g. MLFlow).
Excellent command of Python
Fluent in English and Spanish

Nice to Have Skills.

Experience with machine learning solutions for price optimization, route optimization or document processing is a plus.
Experience with cloudbased AI frameworks like Azure Machine Learning Studio, Google Vertex or AWS Sagemaker is a plus.

What We Offer:

Apart from participating in multiple projects and the opportunity of working with the industry's latest technologies, Cognizant strives to be a great company to work for and you should expect a competitive base salary and various benefits, such as:

International working environment with diverse team
Flexible working hours and hybrid or remote mode.
Yearly Bonus.
Training and career development opportunities: Career path locally and internationally. Specific trainings in both technical and soft skills.
Private healthcare and additional life insurance.
Gympass.
A culture of Respect and Human Empowerment.
Company sponsored activities and partnerships.
Opportunity to be part of a rapidly expanding global organization, within multicultural teams.
Pleasant and inspiring working atmosphere.
Inclusion and diversity in practice.
Employee referral program in place.
Employee volunteering programs and opportunities.
Access to different internal events, communities and initiatives.

Why Cognizant
Cognizant has transformed her clients to deliver the solutions using Digital way of working. In this position, you would leverage your knowledge to shift from traditional way of Agile-DevOps to cloud native adoption.

While doing so you will add value to the client for improving productivity, quality, and time to market in a cost effective way.

You will be working in highly productive SAFe teams and modernize the software delivery processes while focusing on people and technologies.