Data Scientist
@ Solenis

Hyderabad, Telangana, India
₹0
On Site
Full Time
Posted 2 days ago

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Job Details

About Solenis

Solenis is a leading global producer of specialty chemicals, delivering sustainable solutions for water-intensive industries. Owned by Platinum Equity, the company offers advanced water treatment chemistries, process aids, functional additives, and state-of-the-art monitoring systems. With a global presence and a commitment to safety, diversity, and professional growth, Solenis is recognized as a US Best Managed Company.

Global Excellence Center (GEC) - Hyderabad

The GEC in Hyderabad supports global operations in IT, analytics, finance and more. Located in the heart of the IT hub, it provides a dynamic work environment, strong career development, and world-class infrastructure including on-campus gym, recreation facilities, and creche services.

Data Scientist Role Overview

As a Data Scientist at Solenis, you will join the AI & Data Science team to build and deploy Generative AI and Machine Learning solutions. You will work with cutting-edge platforms like Salesforce AgentForce, Google AgentSpace, Snowflake Cortex AI, Snowflake Document AI, and Databricks AutoML across a modern data stack including Snowflake, Databricks, SAP, and Salesforce.

Key Responsibilities

  • Data Analysis & Interpretation: Analyze large datasets and perform exploratory data analysis.
  • Machine Learning & Modeling: Build, train and validate predictive models using ML algorithms.
  • Data Engineering Support: Collaborate with data engineers to clean and prepare data.
  • Visualization & Communication: Create dashboards and present insights to various stakeholders.
  • Cross-Functional Collaboration: Work with product managers, engineers and business teams.
  • Experimentation & A/B Testing: Design experiments and analyze impact using statistical methods.
  • Data Governance & Ethics: Ensure compliance with data privacy regulations and promote responsible AI.

Required Qualifications

5-8 years of experience as a Data Scientist in an enterprise environment with strong skills in Python, SQL, and data integration tools. Hands-on experience with Generative AI frameworks (LangChain, HuggingFace, OpenAI APIs), familiarity with Salesforce AgentForce, Google AgentSpace, and Snowflake Cortex AI. Knowledge of MLOps tools like MLflow, dbt, and Git is essential.

Educational and Preferred Experience

Bachelor’s in Computer Science, Data Science, Statistics or related field required; Master’s or Ph.D. preferred. Experience in chemical, manufacturing or industrial sectors is a plus.

Benefits

  • Free internal and external training courses
  • Self-paced language training
  • Birthday or anniversary gifts
  • Company car, phone, and health benefits
  • Hybrid work arrangement (3 days in office)
  • Additional perks like creche, parking, and relocation assistance

How to Apply

If you are passionate about data science and ready to solve complex challenges, join Solenis and help drive innovation in commercial, supply chain, and customer experience domains. Introduce yourself to our Talent Acquisition team with your resume and a brief note on how you can add value to our team.

Key skills/competency

  • Data Analysis
  • Machine Learning
  • Predictive Modeling
  • Data Engineering
  • Visualization
  • Statistical Analysis
  • Generative AI
  • MLOps
  • Collaboration
  • Data Governance

How to Get Hired at Solenis

🎯 Tips for Getting Hired

  • Research Solenis culture: Study their mission, values, and news.
  • Customize your resume: Align skills with data science requirements.
  • Highlight AI expertise: Emphasize Generative AI and ML projects.
  • Practice technical challenges: Prepare for coding and data analysis tests.

📝 Interview Preparation Advice

Technical Preparation

Review Python libraries and ML algorithms.
Practice SQL queries and data manipulation.
Explore Generative AI frameworks with small projects.
Study deployment best practices in MLOps.

Behavioral Questions

Describe your teamwork experience in technical projects.
Explain managing tight deadlines and project challenges.
Share a complex data problem you solved collaboratively.
Discuss handling feedback and adapting to changes.

Frequently Asked Questions