Data Scientist

Solenis is a leading global producer of specialty chemicals, delivering sustainable solutions for water-intensive industries, including consumer, industrial, institutional, food and beverage, and pool and spa water markets. Owned by Platinum Equity, our innovative portfolio includes advanced water treatment chemistries, process aids, functional additives, and state-of-the-art monitoring and control systems. These technologies enable our customers to optimize operations, enhance product quality, protect critical assets, and achieve their sustainability goals.

At our Global Excellence Center (GEC) in Hyderabad, we support Solenis’ global operations by driving excellence in IT, analytics, finance, and other critical business functions. Located in the heart of the IT hub, the GEC offers a dynamic work environment with strong career development opportunities in a rapidly growing yet stable organization. Employees benefit from world-class infrastructure, including an on-campus gym, recreation facilities, creche services, and convenient access to public transport.

Headquartered in Wilmington, Delaware, Solenis operates 69 manufacturing facilities worldwide and employs over 16,100 professionals across 130 countries. Recognized as a 2025 US Best Managed Company for the third consecutive year, Solenis is committed to fostering a culture of safety, diversity, and professional growth.

For more information about Solenis, please visit


We're Hiring: Data Scientist

Location: Hyderabad India - Hybrid

Full-Time | Permanent Position

What you need to be successful
- Solenis is seeking a technically skilled and enterprise-savvy Data Scientist to join our AI & Data Science team. This role focuses on building and deploying Generative AI and Machine Learning solutions using cutting-edge platforms such as Salesforce AgentForce, Google AgentSpace, Snowflake Cortex AI, Snowflake Document AI, and Databricks AutoML. You’ll work across a modern data stack that includes Snowflake, Databricks, SAP, and Salesforce, helping to drive innovation in commercial, supply chain, and customer experience domains.

Key Responsibilities

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.

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.

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.

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.

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.

Experimentation & A/B Testing
- Design and analyze experiments to test hypotheses and measure impact.
- Use statistical methods to ensure validity and reliability of results.

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.

Some benefits