Structure jobs in India

The Lead - Compensation and Benefits will be responsible for designing, implementing, and overseeing comprehensive compensation and benefits strategies for the organisation. This role requires a deep understanding of industry practices, particularly in the metal industry, to ensure competitive and effective remuneration structures.

A high-impact leadership role to build and lead the Talent Acquisition function for a fast-scaling global organisation, with India headcount expected to grow to 5,000 by year-end. The role requires strategic thinking, global stakeholder management, and experience in setting up scalable TA structures across tech and digital domains.

This is a high-impact role working directly with CXOs on strategic initiatives, business transformation programs, and high-priority projects. The candidate will act as a force multiplier for leadership by bringing structure, strategic insights, and execution rigor to critical business priorities.

• Lead fundraising strategy and execution across equity, debt, and hybrid structures-driving investor outreach, roadshows, and capital closure for ongoing and upcoming impact-focused initiatives.
• Build and manage strategic investor relationships with global LPs, oversee due diligence, and contribute to refining the organization's investment thesis and long-term capital strategy.

Job RequirementsEducation

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)Relevant Experience

* 5 - 7 years for Data Scientist

* Relevant working experience in a data science/advanced analytics roleBehavioural Skills

* Delivery Excellence

* Business disposition

* Social intelligence

* Innovation and agilityExperience

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)

* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

* Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)Roles & Responsibilities

Analytics & Strategy

1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business

2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data

3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions

4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence

1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project

2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems

3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement

1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables

2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats