Senior Data Scientist

Tiger Analytics; España; Presencial; EUR 50.000 - 100.000; Jornada completa

Descripción de la vacante

An established industry player is seeking a skilled Data Scientist to innovate with Machine Learning and AI solutions. This role offers the chance to work on cutting-edge projects in a dynamic environment, leveraging big data technologies to drive AI advancements. You'll collaborate with cross-functional teams to develop and optimize data pipelines, ensuring efficient project execution while adhering to enterprise standards. With a focus on MLOps and automation, this position promises significant career growth and the opportunity to make a real impact in the field of data science. If you're passionate about technology and eager to tackle complex challenges, this role is perfect for you.

Formación

• 8+ years of experience in Data Science and Machine Learning.
• Hands-on experience with Python, PySpark, and SQL for data querying.

Responsabilidades

• Develop and deliver Advanced Analytics/Data Science solutions.
• Collaborate with data engineers to optimize analytics capabilities.

Conocimientos

Data Science

Machine Learning

Python

PySpark

Statistical Analysis

Problem-Solving

Stakeholder Management

Educación

Bachelor’s degree in Computer Science

Master’s degree in Mathematics

Herramientas

Azure Machine Learning

Databricks

Azure Data Factory

GitHub

Descripción del empleo

Tiger Analytics is the largest AI and advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring depth in the industry and deep expertise in Data Science, Data Engineering, Machine Learning, and AI. Various market research firms, including Forrester and Gartner, have recognized our business value and leadership. We are headquartered in Silicon Valley and have our global delivery center in Chennai, India. We also have a presence in Europe, Singapore and LATAM markets.

We are looking for a skilled Data Scientist to develop Machine Learning (ML) and Artificial Intelligence (AI) solutions. The role involves working on ML/AI projects using advanced analytics tools in a CI/CD environment. The ideal candidate will leverage big data technologies or open-source platforms to drive AI-driven innovations.

Key Responsibilities:

1. Develop and deliver Advanced Analytics/Data Science solutions, focusing on DevOps/MLOps and Machine Learning models.
2. Collaborate with data engineers and ML engineers to process and analyze data, optimizing analytics capabilities.
3. Ensure timely and cost-effective project execution while adhering to enterprise architecture standards.
4. Build and optimize data pipelines using big data technologies, including batch and real-time processing.
5. Automate ML models deployment and the end-to-end ML lifecycle using Azure Machine Learning and Azure Pipelines.
6. Monitor ML infrastructure by setting up cloud alerts, dashboards, and logging mechanisms.
7. Troubleshoot and optimize machine learning infrastructure for scalability and efficiency.

Minimum Requirements:

1. 8+ years of experience in Data Science and Machine Learning.
2. 5+ years of hands-on experience in Python and PySpark.
3. 4+ years of experience in Machine Learning (ML), with cloud service expertise (Azure preferred, AWS/GCP is a plus).
4. Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
5. Strong stakeholder management skills, including engagement with business units and vendors.
6. Data Science: Strong expertise in developing supervised and unsupervised ML models, with knowledge of time series and demand forecasting being a plus.
7. Programming: Hands-on experience with Python, PySpark, and SQL for data querying and statistical modeling.
8. Statistics: Solid understanding of statistical tests, distributions, regression models, and maximum likelihood estimators.
9. Cloud & Big Data: Experience in Databricks, Azure Data Factory (ADF), and familiarity with Spark, Hive, and Pig is advantageous.
10. ML Deployment: Experience in deploying ML models, working with version control tools like GitHub, and implementing CI/CD pipelines.
11. MLOps & Automation: Understanding of MLFlow, Kubeflow, and ML Ops automation frameworks.
12. Problem-Solving: Strong analytical skills to handle complex data science challenges in commercial, net revenue management, or supply chain domains.
13. Bias for action, with the ability to deliver outstanding results through task prioritization and time management.
14. Be proactive, curious, can-do attitude, flexible personality.

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.