Data Scientist

Role Overview

The role requires 4+ years of experience in data science, machine learning, or a related field. The candidate should have strong hands-on experience in machine learning and statistics, focusing on structured and unstructured data problems. The candidate should also have practical experience in several areas, including time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, and ElasticNet.

What You Will Do

The candidate will integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow. They will also develop and maintain MLOps pipelines for automated model training, testing, deployment, and monitoring.

Why It Might Be a Fit

The candidate should have excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail. They should also have a strong understanding of challenges in business areas, applicability of relevant data science disciplines, and system interactions.

Requirements

• 4+ years of experience in data science, machine learning, or a related field
• Strong hands-on experience in machine learning and statistics
• Practical experience in several areas, including time series forecasting, clustering and classification techniques, regression, boosting algorithms, optimization techniques, NLP, recommendation systems, and ElasticNet
• Excellent programming skills in Python/Py spark and SQL
• Understanding of developing, implementing, deploying machine learning models on cloud platforms (Azure, AWS, GCP)
• Integrate machine learning models into existing systems and applications, ensuring seamless functionality and data flow
• Understanding of developing and maintaining MLOps pipelines for automated model training, testing, deployment, and monitoring
• Understanding of monitoring and analysing model performance, providing reports and insights to stakeholders as needed
• Familiarity with data processing and storage tools, such as SQL, Hadoop, or Spark
• Advanced engineering abilities to deliver flexible and scalable end-to-end machine learning solutions
• Exposure to data visualization software and packages (Power BI, Tableau, matplotlib, d3)
• Excellent written and verbal communication skills, confidence in presenting ideas and findings to stakeholders, and ability to do so at the right level of detail

Tagged as: Data Visualization, Forecasting, Power BI, Python, SQL, Tableau