Eucloid - Data Scientist - Machine Learning

• 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.

(ref:hirist.tech)