Data Scientist (work remotely in Spain)

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UL

Data Scientist (work remotely in Spain)

Thousands of us around the world wake up every day with a common purpose to make the world a safer, more secure and sustainable place. Science is in our DNA; we are endlessly curious and passionate about seeking and speaking the truth. We take delight in knowing that our work makes a meaningful contribution to society, and we are proud that our culture is centered on integrity, collaboration, inclusion and excellence. UL stands at the forefront of technological advancement, and we are continually challenged to find new ways to foster innovation and positive change. Satisfying? Yes. Exciting? Absolutely!

As our global footprint continues to spread across the world, we are looking for a Data Scientist to join our AILab based in Spain. Depending on your preference you could work remotely or as a hybrid between office / home work.

In this role you will have a strong focus enabling UL’s client base to effectively leverage recent developments in the digital revolution, giving them the ability to truly leverage their own corpus of data combined with 3rd party data sources, UL’s core data sources and deep Voice of Science competences, to win in a rapidly evolving digital eco-system.

You’ll already have some great experience in machine learning and development best practices and be someone that is passionate about working with data and driven to deliver creative and compelling solutions which turn data into actionable information for our customers.

  • Work on data ingest, data enrichment, analytics, machine learning and artificial intelligence.
  • Responsible for designing and developing innovative analytical solutions, which drive business insights within our products.
  • Understand and use computer science fundamentals, including data structures, algorithms, computability and complexity and computer architecture
  • Use exceptional mathematical skills, in order to perform computations and work with the algorithms involved in this type of programming
  • Produce project outcomes and isolate the issues that need to be resolved, in order to make programs more effective
  • Manage end-to-end data modelling, development and production of applications (including, but not limited to, the machine learning algorithms) being created
  • Work at the intersection of our data engineering, data science, software engineering and UX teams and help us build our evolving analytical platform using machine learning services
  • Apply machine learning algorithms and libraries for problem solving skills with an emphasis on product development
  • Communicate and explain complex processes to people who are not programming experts
  • Liaise with stakeholders to analyse business problems, clarify requirements and define the scope of the resolution needed
  • Research and implement best practices to improve the existing machine learning infrastructure
  • Provide support to engineers and product managers in implementing machine learning in the product
  • Creating automated machine learning services/systems and constant tracking of its performance
  • Master’s/PhD degree or equivalent work experience in Data Analytics, Data Science, Computer Science or any other related field of science
  • Strong problem solving skills with an emphasis on R&D and product development.
  • Experience querying databases and using statistical computer languages Python, R, SQL, etc.
  • Experience using statistical computer languages (Python, R, SQL, etc.) to manipulate data and draw insights from large data sets.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Excellent written and verbal communication skills for coordinating across teams.
  • A drive to learn and master new technologies and techniques.
  • Detailed knowledge of machine learning evaluation metrics and best practice
  • Strong Python coding skills and problem-solving, good analytical & communication skills
  • Solid grasp of A/B testing knowledge and extensive experience with hypothesis testing.
  • Demonstrated effective interpersonal, influencing, collaboration and listening skills
  • Experience of working in an Agile environment for applied research
  • Experience with Azure Machine Learning Studio, Azure DevOps, and CICD.
  • Proficiency in English language.
  • Mission For UL, corporate and social responsibility isn’t new. Making the world a safer, more secure and sustainable place has been our business model for the last 125 years and is deeply engrained in everything we do.
  • People Ask any UL employee what they love most about working here, and you’ll almost always hear, “the people.” Going beyond what is possible is the standard at UL. We’re able to deliver the best because we employ the best.
  • Interesting work Every day is different for us here as we eagerly anticipate the next innovation that our customers’ create. We’re inspired to take on the challenge that will transform how people live, work and play. And as a global company, in many roles, you will get international experience working with colleagues around the world.
  • Grow & achieve We learn, work and grow together with targeted development, reward and recognition programs as well as our very own UL University that offers extensive training programs for employees at all stages, including a technical training track for applicable roles.
  • Total Rewards Competitive remuneration, annual bonus, annual paid leave. 2 Volunteer Days off per year to spend participating in an array of volunteer activities. Flexible and remote working arrangements

Working at UL is an exciting journey that twists and turns daily. We thrive in the twists and revel in the turns. This is our every day. This is our normal. Curious? To learn more about us and the work we do, visit https//www.ul.com/

Por favor, para apuntarte a este trabajo visita www.linkedin.com.