Data Scientist

About the role

We are hiring a hands-on Data Scientist with 4–6 years of experience building and shipping classical machine-learning models on enterprise business data. The role sits in a central AI team at an enterprise client that serves the whole business, so the problems change with demand: sales, marketing, pricing, operations, procurement, HR, finance.

What you'll do

• Pick up problems from any function as the business needs them and frame them as supervised-learning tasks — e.g. deal win/loss and churn classification
• Build, tune and validate models end to end: feature engineering, model selection, cross-validation, hyperparameter tuning, calibration and error analysis
• Work with structured enterprise data from CRM, ERP, product master and finance systems — profiling, cleaning, joining and resolving data-quality gaps before modelling
• Run exploratory analysis and statistical tests (hypothesis testing, A/B analysis, causal reasoning) to back recommendations with evidence
• Explain model behaviour to business stakeholders using interpretability techniques (SHAP, feature importance, partial dependence) and plain-language insight

What you need

• 4–6 yrs of experience
• Machine learning
• SQL
• LLMs
• Python
• Pandas
• Scikit-learn
• MBA

Good to have

• Azure
• HR operations
• Salesforce
• MLOps
• Databricks
• Spark