Eucloid - Data Scientist - Machine Learning

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.
(ref:hirist.tech)

Work arrangement
No