About the role
- 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.
- 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.
- 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.
- 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.
- Access to a huge array ofinternal and external training courses(free).
- Access toself-paced language training(free).
- Birthday or wedding anniversary giftof INR 1500.
- Annualcharity work dayto give back to the community.
- Company car/phone(if required for role).
- Competitivehealth & wellness benefit plan.
- Continuous professional developmentwith numerous growth opportunities.
- Onsitecreche facility.
- Employee Business Resource Groups (EBRGs).
- Electric car charging stationsat office.
- Hybrid work arrangement(3 days office, 2 days WFH).
- Internet allowance.
- No-meeting Fridaysfor focused work.
- Free parkingon site.
- Relocation assistance(if applicable).
- Staff hangout spaces– enjoy carrom, chess, and more.
- Office well-connected to public transport (just 10 min walk).