Lead Data Scientist

Dow has an exciting opportunity for a Lead Data Scientist in Diamond System Analytics, Information Technology team, located in Auburn, MI or Houston, TX!

The Lead Data Scientist will work with a cross-functional team whose objective is to deliver analytics solutions to help drive business value at Dow. The lead data scientist will help identify new analytics opportunities and lead the design and development of analytics solutions. Projects can include existing Analytics model and/or enhancements of advanced models in different business or functional domains. We are seeking candidates who have expertise in one or more of the following areas: Optimization, Forecasting, Text mining, deep learning, AI/ML solution development as well as programming experience.   

The Lead Data Scientist will work with a multi-disciplinary IT team (analysts/designers/developers/support) to: 

• Create valuable contributions to analytics projects. 

• Lead data analysis to develop solutions in Azure or other analytics tools emphasizing efficiency, reliability and automation. 

• Identify opportunities for innovating with digital capabilities aiming to accelerate Dow’s digital transformation. 

Job Responsibilities: 

• Demonstrating effective analytical and problem-solving abilities. 

• Ability to break down and understand complex business problems, define a solution, and implement it using advanced quantitative methods. 

• Hands-on experience with programming languages for data analysis, ideally Python, SQL, or R. 

• Experience with different data models, data analytics techniques, Machine learning and AI algorithms.  

• Experience with data extraction, data manipulation and data visualization techniques. 

• Leading the design and development of end-to-end data science analytics solutions using associated technologies.  

• Communicating data-driven recommendations to the stakeholders to enable the business objective. 

Other Critical Skills: 

• Ability to thrive in challenging situations and solve complex problems. 

• Innate and insatiable curiosity about emerging technologies, with the ability to quickly learn and exploit cutting-edge offerings to achieve business objectives. 

• Expertise in delivering multiple analytics solutions or applications/tools. 

• Ability to take initiative and deliver results.

The successful applicant should be able to show expertise in some of these areas: 

• Development of machine learning models, validation and maintenance using Python. 

• Data preprocessing, harmonization, and feature engineering to prepare modeling datasets. 

• Knowledge of cloud computing environment such as Microsoft Azure required for developing and implementing data science solutions.   

• Supervised and unsupervised learning techniques.

• Deep learning techniques.

Required Qualifications: 

• A minimum of a PhD in Data Science, Business Analytics, Computer science, Statistics, or other relevant discipline.

• A minimum 3 years of experience in data analytics, modeling, machine learning, or other related field.

• Hands-on experience on data science projects including querying databases using SQL, programming, analytics model development and implementation, using Python, R, or equivalent environment (Pandas, NumPy, SciPy, and Scikit-learn).

Preferred Qualifications: 

• Experience developing in the Azure environment.

• Knowledge of one or more business domains such as supply chain, marketing, finance. 

Note: Relocation assistance is not available with this position.