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L
Linde
Data Scientist
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$110,146 / year median in the U.S.
+15% projected growth
Job Description
Linde Inc. Data Scientist Danbury, CT, United States | req32332 What you will enjoy doing• Collaborate with business partners to understand system and operational requirements and define appropriate technical solutions Support and administer enterprise systems and technical platforms while leading technical development of tools and processes that enhance system performance, monitoring, and decision support Stay abreast of new technology and actively contributing ideas for system improvements, infrastructure enhancements, and administrative tools. Balance implementation and configuration of system solutions with replication and maintenance, monitoring, and support of existing systems and tools Utilize technical skills to develop scripts, utilities, and system automation tools in order to increase productivity and efficiency within the business. Write code and design database schemas for applications and system-related data structures Write SQL queries to analyze data and support system operations, utilizing technologies, including Python and Tableau, to create visualizations in order to clearly display system performance metrics and operational data to business users Write Python scripts used for systems administration, automation, and back-end operational processes Remote work permitted from any location in the U.S. What makes you great Must have a Master's degree or foreign equivalent in Computer Science, or a related field Coursework/graduate research experience must include: Programming expertise with Python in a consulting role working directly with clients to solve a wide range of complex problems; Utilizing database schema design, complex query optimization, and data creation to enable actionable business insights, specifically in parsing and transforming raw data into structured formats— with tools like Regular Expressions —to support efficient querying, analysis, and automated processing workflows Designing and developing scalable and sustainable back-end applications, including creating and integrating RESTful APIs for seamless communication, and ensuring software quality through robust unit and integration testing using frameworks such as PyTest or GoogleTest or other testing frameworks Translating complex data into actionable insights by creating interactive data visualizations and dashboards using tools such as Tableau or Python visualization libraries (plotly, matplotlib, seaborn) Developing responsive, and user-friendly interfaces for mobile and web applications using JavaScript frameworks and leveraging containerization technologies like Docker to configure and deploy microservices