Básico

Senior Data Scientist

catalunya, Spain Compañía: JR Spain Cliente / Empleador: Tiger Analytics
Publicado: 28.05.2026
Fecha de cierre: 12.07.2026
Referencia laboral: 510132310275155558432460

Información del puesto

Ubicación
catalunya, Spain
Compañía
JR Spain
Cliente / Empleador
Tiger Analytics
Referencia laboral
510132310275155558432460
Tipo de listado
Básico
Se requiere permiso de trabajo de la UE
No
Publicado
28.05.2026
Fecha de cierre
12.07.2026

Descripción del puesto

Tiger Analytics is looking for an experienced Senior Data Scientist to join our team. As a leading advanced analytics consulting firm, we help Fortune 500 companies generate valuable insights from their data. With our deep expertise in Data Science, Machine Learning, and AI, we deliver innovative solutions to complex business problems. As a Senior Data Scientist at Tiger Analytics, you will have the opportunity to work on cutting-edge projects, collaborate with cross-functional teams, and drive business value through advanced analytics.

Key Responsibilities:

  • Work on the latest applications of data science to solve business problems.
  • Effectively communicate the analytics approach and how it will meet and address objectives to business partners.
  • Lead analytic approaches; integrate solutions collaboratively into applications and tools with data engineers, business leads, analysts, and developers.
  • Create repeatable, interpretable, dynamic, and scalable models seamlessly incorporated into analytic data products.
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists.
  • Stay connected with external sources of ideas through conferences and community engagements.
  • Support demands from regulators, investor relations, etc., to develop innovative solutions to meet objectives utilizing cutting-edge techniques and tools.

Requirements

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
  • Minimum of 5 years of experience in Data Science and Machine Learning.
  • Solid understanding of machine learning algorithms and statistical analysis.
  • 2-3 years of Model building and Enterprise-level deployement experience.
  • Proficiency in Python and PySpark programming languages commonly used in Data Science.
  • Experience with cloud platforms such as Azure and AWS is a plus.
  • Ability to preprocess and clean large datasets for analysis.
  • Strong problem-solving skills and ability to think analytically.
  • Excellent communication and presentation skills.
  • Ability to work effectively in cross-functional teams and manage multiple projects simultaneously.
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Habilidades

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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