At ADS, no idea is off limits, and we celebrate creativity and bold moves. For more than 50 years ADS has been manufacturing a variety of innovative and environmentally friendly alternatives to traditional materials. Headquartered in Hilliard, Ohio, we are a multi-billion dollar stormwater management company, manufacturing pipe and ancillary products. What does that mean? When it storms, we capture rain with our drain basins, convey it with pipe, store it using chambers and finally treat it with our water quality products, before safely returning water back to the environment. We handle, what we call, the entire lifecycle of a raindrop. Our products help prevent flooding, which increases quality of life for people living in large cities, suburbs, and rural towns. We also believe in creating a circular economy and are the largest plastic recycling company in North America. We use plastic shampoo and detergent bottles to create pipe, diverting over 500 million pounds of plastic from landfills every year. ADS operates a global network of over 60 manufacturing plants and 30 distribution centers.

We have amazing stories to tell, and we need your help getting our story out there. To learn more about ADS, please visit our website at www.adspipe.com.

As a Data Scientist, you will play a crucial role in developing and implementing advanced data analytics and machine learning models to extract valuable insights from complex datasets. Your work will directly impact critical business decisions and contribute to the continuous improvement of our products and services. We are looking for a talented individual with a strong analytical mindset, solid programming skills, and a passion for tackling challenging problems using data-driven techniques.

Primary Job Responsibilities:

The responsibilities of this position include, but are not limited to:

+ Data Analysis: Collect, process, and clean large datasets from various sources to ensure data accuracy and integrity.

+ Machine Learning Modeling: Design, develop, and deploy predictive and prescriptive models using state-of-the-art machine learning algorithms to solve business problems and enhance product features.

+ Statistical Analysis: Apply statistical methods and hypothesis testing to analyze data and draw meaningful conclusions.

+ Data Visualization: Create visually compelling and insightful data visualizations to communicate complex findings to stakeholders effectively.

+ Feature Engineering: Identify relevant features and apply feature engineering techniques to improve model performance and accuracy.

+ Model Evaluation: Evaluate model performance through metrics, testing, and validation, and iteratively optimize models for better results.

+ Collaborate with cross-functional teams: Work closely with engineering, product, and business teams to understand requirements, formulate data-driven solutions, and implement these solutions into real-world applications.

+ Research and Innovation: Stay abreast of the latest trends and advancements in data science, machine learning, and artificial intelligence to propose and implement cutting-edge techniques.

+ Data Security and Privacy: Ensure compliance with data security and privacy regulations throughout the data analysis and model development process.

Job Skills:

+ Experience in hypothesis testing, confidence intervals and design of experiments.

+ Experience in data mining including cleaning and validating data.

+ Ability to use Decision trees, linear and non-linear regression, logistic regression, models and classification techniques for data analysis and clustering.

+ Knowledge of most of the following quantitative fields: Natural Language Processing, Information Retrieval, Machine Comprehension, Question Answering/Conversational AI, Reinforcement Learning, Knowledge Graph, Causal Inference, and Design of Experiment.

+ Proficiency in programming languages such as Python/R for data manipulation and analysis.

+ Experience with data manipulation libraries (e.g., Pandas) and machine learning frameworks (e.g., scikit-learn, TensorFlow, or PyTorch).

+ Experience with DevOps, Agile/SCRUM methodology and techniques.

+ Experience with Oracle Demand Planning and E-Business suite applications and Salesforce.

+ Excellent written and verbal communication skills.

+ Ability to work effectively with remote teammates and users.

+ Familiarity with data visualization tools (Power BI/Tableau) and Microsoft BI tooling, including Azure.

+ Knowledge and experience with data privacy laws and regulations (i.e. California Consumer Privacy Act (CCPA), General Data Protection Regulation (GDPR))

Requirements:

+ Advanced degree (Master's/Ph.D.) in Data Science, Statistics, or related field.

+ Minimum 3 years of experience as a Data Scientist, with a demonstrated focus on demand planning, preferably in Manufacturing.

+ Experience with Big Data technologies (e.g., Hadoop, Spark) and cloud computing platforms (e.g., AWS, Azure, GCP).

+ Experience in developing production-grade machine learning models and deploying them into real-world applications.

+ Understanding of supply chain operations, demand forecasting methodologies, and inventory management principles.

ADS supports an inclusive workplace that values diversity of thought, experience, and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. ADS is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.

Requisition ID: 2023-15293

External Company Name: Advanced Drainage Systems

External Company URL: http://www.ads-pipe.com/en/

Street: 3455 Mill Run Drive