Full-Time Data Scientist

We seek a dynamic and experienced Data Scientist to play an integral role in developing and enhancing LGC's data science product portfolio. As a pivotal member of our innovative R&D team, you will collaborate closely with multiple divisions within LGC, leveraging your data science expertise to deliver impactful insights and advanced solutions.

Job Responsibilities:

• Work with multiple partners throughout the organization to identify valuable data sources and automate collection processes
• Undertake pre-processing, curating, and model building of the structured and unstructured data
• Analyze large datasets to discover trends and patterns
• Help identify and define new product ideas based on the outcomes from the predictive models and machine-learning algorithms
• Present analytical results using data visualization techniques
• Propose data science solutions and strategies for R&D and business challenges
• Taking ideas from theory into deployment
• Attend meetings, conferences, symposia, and seminars to promote LGC capabilities and to stay on top of scientific/technological developments
• Meticulously learn, diligently follow, and deliver high-quality product development documentation consistent with LGC’s quality systems
• Follow company requirements of the ISO 13485 quality management system

Qualifications:

Minimum Qualifications:

• Ph.D or M.S or equivalent experience with at least 3-5 years of industry/academic experience in data science, mathematics, computer science, physics, biostatistics, computational biology, operations research, or a related field
• Ability to break down and understand complex business/scientific challenges, define solutions, and implement them using advanced quantitative methods
• Proficiency in high-level scripting languages (Python, Java)
• Experience in low-level programming languages (C/C++)
• Experience with data analysis and visualization tools (R, matplotlib, or similar)
• Experience with LINUX-based operating systems and shell scripting
• Expertise in supervised and unsupervised learning methods
• Knowledge and experience in statistical and data mining techniques: Clustering, GLM/Regression, Random Forest, Boosting, Trees, text mining, network analysis, etc.
• Ability to analyze algorithms
• Knowledge of software development principles and architecture
• Basic computer skills, including working knowledge of Microsoft Office suite of products, particularly Word, Excel, PowerPoint, and Visio

Preferred Qualifications:

• Understanding of deep learning and LLM algorithms
• Knowledge of probability, Bayesian statistics, and neural networks
• Experience in Cloud technologies such as AWS, Azure, or GCP
• Knowledge of any relational database such as My SQL

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