Sr Specialist Digital Innovation

Overview 综述

Celanese is a global leader in chemistry, producing specialty material solutions used across most major industries and consumer applications. Our businesses use our chemistry, technology and commercial expertise to create value for our customers, employees and shareholders. We are committed to sustainability by responsibly managing the materials we create for their entire lifecycle and are growing our portfolio of sustainable products to meet increasing customer and societal demand. We strive to make a positive impact in our communities and to foster inclusivity across our teams. Celanese is a Fortune 500 company that employs approximately 12,400 employees worldwide with 2023 net sales of $10.9 billion.

Responsibilities 职责

We are looking for a Data Scientist who will support the Celanese custom Grade Selection Product Finder with insights gained from analyzing company data. The ideal candidate is adopt at using large external and internal data sets to find opportunities for the credit process optimization/automation as well as identifying sales opportunities and using models to recommend the courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams in a global setting. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms to apply to data sets.

Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.

Develop company A/B testing framework and test model quality.

Coordinate with different functional teams to implement models and monitor outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.

Qualifications 要求

Strong experience with programming languages such as R, Python, and SQL. Ability to manipulate data and draw insights from large datasets.

Strong coding skills in languages relevant to machine learning and data science, such as Python. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries specifically designed for working with LLMs, RAG, and LMMs.

Profound knowledge and hands-on experience with Large Language Models (LLMs), including but not limited to models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), and their derivatives.

Understanding of the underlying mechanisms, strengths, limitations, and ethical considerations of LLMs.

Demonstrated experience with RAG techniques and their applications. Ability to leverage RAG for enhancing the performance of language models by combining the power of retrieval and generative capabilities to provide more accurate, contextually relevant, and information-rich responses.

Solid understanding and practical application of LMMs in analyzing data that have multiple levels of correlation or non-constant variability. Experience in applying LMMs to complex datasets to account for both fixed and random effects, ensuring accurate data interpretation and decision-making.

Experience in preprocessing, cleaning, and structuring large datasets to make them suitable for use with advanced models like LLMs and RAG systems. Ability to efficiently manage and manipulate big data sets, ensuring high-quality inputs for model training and analysis.

Solid understanding and application experience with a wide array of machine learning techniques, including but not limited to clustering, decision tree learning, and artificial neural networks, and an understanding of their real-world advantages and limitations.

Deep knowledge of advanced statistical techniques and concepts (regression analysis, distribution properties, statistical testing, etc.) and experience applying these techniques to data analysis and modeling. Experience with data mining techniques such as GLM/Regression, Random Forest, Boosting, Trees, text mining, and social network analysis.

Ability to apply critical thinking and problem-solving skills to leverage LLMs, RAG, and LMMs in addressing complex business challenges. Capability to design and implement models that effectively analyze data, predict outcomes, and provide insights.

Demonstrated ability to approach complex problems methodically to derive actionable insights and solutions.

Excellent verbal and written communication skills, with the ability to clearly articulate complex concepts and findings to both technical and non-technical stakeholders. Proven ability to collaborate effectively with cross-functional teams to drive projects to completion.

Ability to work independently with experts from different fields, including chemical engineers, process engineers, and environmental scientists, to integrate diverse data sources and insights.

7+ years of experience manipulating data sets and building statistical models, has a Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science or another quantitative field.

Knowledge of coding APIs and experience with several languages like JavaScript, and open-source frameworks like Streamlit.

Experience with cloud services (AWS, Azure, Google Cloud), Cloud data warehouse (Snowflake) and understanding of how to leverage them for scalable data analysis.

Proficiency in data visualization tools and libraries (e.g., PowerBI, Matplotlib, Seaborn) to communicate findings visually.

Experience using Alteryx to analyze and manipulate data.

Knowledge of data architecture and pipelines, including experience with big data technologies and database management systems.

Knowledge of SAP and Salesforce a plus.

Background in Chemistry a plus.

Regular Full-Time