Job Description :

- Analyze structured and unstructured datasets to identify actionable insights, patterns, and trends.

- Develop and deploy machine learning models and statistical solutions to address business challenges.

- Apply statistical techniques including hypothesis testing, probability modeling, and model evaluation metrics such as ROC-AUC, Precision/Recall, RMSE, etc.

- Collaborate with data engineers to design scalable data pipelines and data architectures.

- Translate complex analytical findings into clear, actionable recommendations for business stakeholders.

- Contribute to building data-driven tools, analytical solutions, and dashboards for clients.

- Support the deployment, monitoring, and performance tracking of machine learning models in production environments.

- Maintain documentation of methodologies, experiments, models, and results to ensure reproducibility and governance.

- Work with version control systems such as Git and ML lifecycle tools to manage model development and deployment workflows.

- Stay updated on emerging trends in AI/ML and apply relevant techniques and best practices to projects.

Qualifications :

Academic Background :

- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Technical Expertise :

- 3 - 5 years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics.

- Strong SQL skills for data extraction, transformation, analysis, and manipulation.

- Solid understanding of statistics, probability, and model evaluation techniques.

- Experience with machine learning algorithms including regression, classification, clustering, and tree-based models.

- Experience developing and deploying production-level machine learning solutions.

- Familiarity with ML frameworks and libraries such as Scikit-learn or TensorFlow.

- Familiarity with MLOps practices and ML lifecycle management would be preferred.

- Experience with data visualization tools such as Tableau, Power BI, or Looker.

- Experience working with cloud-based data platforms such as Databricks would be preferred.

- Basic understanding of deploying models and working with large-scale data platforms.

- Experience with Git or similar version control systems.

Skills :

- Strong problem-solving and analytical mindset with the ability to work effectively in agile environments.

- Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

- Strong collaborative skills with experience working across cross-functional teams.

- Ability to translate business requirements into analytical solutions and actionable insights.

- Experience working in production environments with exposure to monitoring, maintaining, and improving deployed machine learning models.