Key Responsibilities 1. Data Analysis & Interpretation Analyze large datasets to extract actionable insights. Use statistical techniques to identify trends, patterns, and anomalies. Perform exploratory data analysis (EDA) to understand data distributions and relationships. 2. Machine Learning & Modeling Build, train, and validate predictive models using machine learning algorithms. Select appropriate modeling techniques based on business problems. Continuously improve models through feature engineering and hyperparameter tuning. 3. Data Engineering Support Collaborate with data engineers to ensure data pipelines are robust and scalable. Clean, transform, and prepare data for analysis and modeling. Work with structured and unstructured data from various sources. 4. Visualization & Communication Create dashboards and visualizations to communicate findings to stakeholders. Translate complex data insights into clear, actionable recommendations. Present results to both technical and non-technical audiences. 5. Cross-Functional Collaboration Work closely with product managers, engineers, and business teams. Understand business objectives and align data science efforts accordingly. Participate in strategic planning and decision-making processes. 6. Experimentation & A/B Testing Design and analyze experiments to test hypotheses and measure impact. Use statistical methods to ensure validity and reliability of results. 7. Data Governance & Ethics Ensure compliance with data privacy regulations and ethical standards. Promote responsible AI and fair use of data. Required Qualifications 5–8 years of experience as a Data Scientist in a large enterprise environment. Demonstrated experience solving enterprise business problems using AI models, including predictive analytics, intelligent agents, and document intelligence. Proficiency in Python and SQL; experience with Snowflake, Databricks, and SAP data integration. Hands-on experience with Generative AI frameworks (e.g., LangChain, HuggingFace, OpenAI APIs) and LLM deployment strategies. Familiarity with Salesforce AgentForce, Google AgentSpace, and Snowflake Cortex AI is highly desirable. Experience with MLOps tools and practices such as MLflow, dbt, and Git. Educational Requirements Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related field. Master’s degree or Ph.D. preferred, especially with a focus on Machine Learning, Artificial Intelligence, or Applied Mathematics. Preferred Experience Experience in chemical, manufacturing, or industrial sectors. Exposure to AI use cases in commercial operations, supply chain, or customer service. Familiarity with SAP-Salesforce integration tools (e.g., Enosix, MuleSoft). Understanding of AI governance, data quality, and master data management frameworks.

About Solenis

Solenis is a leading global provider of water and hygiene solutions. The company’s product portfolio includes a broad array of water treatment chemistries, process aids, functional additives, cleaners, disinfectants, and state-of-the-art monitoring, control and delivery systems. These technologies are used by customers to improve operational efficiencies, enhance product quality, protect plant assets, minimize environmental impact, and create cleaner and safer environments. Headquartered in Wilmington, Delaware, the company has 78 manufacturing facilities strategically located around the globe and employs a team of ~23000 professionals in 160 countries across six continents. Solenis is a 2025 Best Managed Company Gold Standard honoree.