Data Scientist/Data Engineer

Responsibilities

• Engage with clients to understand business goals, data challenges, and requirements, and translate them into scalable data and analytics solutions.
• Design and implement data architecture, ETL/ELT pipelines, data integration, and data platforms to support analytics, AI, and machine learning use cases.
• Perform data analysis, exploratory data analysis, feature engineering, statistical analysis, and predictive modeling to generate actionable business insights.
• Develop, evaluate, and support machine learning models, from data preparation and experimentation through deployment and monitoring.
• Ensure data quality, governance, security, and reliability across data and analytics solutions.
• Collaborate with AI Engineer, Analysts, and Software Engineer to deliver end-to-end solutions.
• Lead project teams, manage timelines and deliverables, and communicate technical and analytical concepts to clients and stakeholders.
• Mentor junior team members and stay up to date with emerging technologies in Data Engineering, Data Science, AI, and Cloud.
• Other tasks as assigned.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or related fields.
• Proven experience in Data Engineering, Data Science, Analytics, or Data/AI Consulting.
• Strong Python or Scala skills with experience in data processing, analysis, and automation.
• Strong knowledge of SQL, data modeling, ETL/ELT, databases, and scalable data pipelines.
• Experience with Apache Spark, Kafka, Airflow, or similar technologies.
• Experience in machine learning, statistical analysis, predictive modeling, and data visualization.
• Familiarity with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch is a plus.
• Experience with AWS, Azure, or GCP is a plus.
• Strong analytical, problem-solving, communication, and client-facing skills.
• Experience leading projects or multidisciplinary teams is a plus.