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Data Scientist
3 months ago
Scope:
The Data Scientist will be responsible for designing, developing, and deploying machine learning models to improve the performance of our products.
Our current technical environment:
Programming languages:
Python, R, Scala
Machine Learning frameworks and libraries:
TensorFlow, PyTorch, scikit-learn
Data visualization tools:
Power BI, matplotlib, seaborn
Statistical analysis, probability theory, and mathematical optimization
- SQL and NoSQL databases
Big data technologies:
Hadoop, Spark
What you'll do:
Design, implement, and continuously improve algorithms for predictive modelling, classification, clustering, and anomaly detection.
Develop and maintain advanced statistical and machine learning models, extracting insights from large datasets to inform business strategies.
Lead data science projects from conception through deployment and monitoring, ensuring collaboration with cross-functional teams.
Develop and maintain scalable data pipelines and ETL processes, ensuring data quality and integrity across various sources.
Prepare comprehensive documentation for data models, algorithms, and processes.
Analyse complex data sets to identify trends and communicate findings through presentations, reports, and dashboards.
What we are looking for:
6 to 8 years of experience in data science, machine learning, or a related field.
Masters or Graduation in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Excellent communication skills, with the ability to present complex technical concepts to non-technical stakeholders.
Proven experience in developing and deploying machine learning models at scale.
Proficiency in programming languages such as Python, R, or Scala.
Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Experience with data visualization tools (e.g., Power BI, matplotlib, seaborn).
Deep understanding of statistical analysis, probability theory, and mathematical optimization.
Ability to perform data wrangling and feature engineering on large datasets.
Experience with SQL and NoSQL databases.
Familiarity with big data technologies such as Hadoop, Spark, or similar platforms.
Hands-on experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques.
Experience of implementing and fine-tuning LLMs for business applications.
- Relevant certifications in data science, machine learning, or artificial intelligence.
Our Values
If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers.
Does your heart beat like ours? Find out here:
Core Values
Diversity, Inclusion, Value & Equality (DIVE) is our strategy for fostering an inclusive environment we can be proud of.
Check out Blue Yonder's inaugural Diversity Report which outlines our commitment to change, and our video celebrating the differences in all of us in the words of some of our associates from around the world.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.