Data Scientist

Role Overview

We are looking for a Data Scientist to help analyze our growing data, build data-driven solutions, and deliver actionable insights that will support key business decisions and innovations across teams.

Responsibilities

• Collect, clean and preprocess structured/unstructured data from multiple sources
• Analyze large datasets to discover trends, patterns and insights that can drive strategy
• Build and train predictive / statistical / machine-learning models to solve business problems
• Design and implement data pipelines / ETL workflows where necessary
• Visualize and communicate findings via reports or dashboards to both technical and non-technical stakeholders
• Collaborate with product, engineering, and business teams to identify opportunities for data-driven features and solutions
• Monitor and maintain the performance, reliability, and integrity of data models (especially those in production)
• Stay updated with the latest developments in data science / analytics / ML and apply them when relevant

Requirements

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Mathematics or related field
• Proficiency in Python (or R), data manipulation libraries, and SQL (or equivalent database/querying tools)
• Strong knowledge of statistics, machine learning / modeling techniques, and data analysis fundamentals
• Experience working with large and complex datasets; data cleaning and preprocessing experience
• Analytical mindset, problem-solving skills, attention to detail
• Good communication skills, ability to turn technical results into actionable business insights
• Ability to collaborate well with cross-functional teams

Nice to Have

• Familiarity with data visualization tools (Tableau, Power BI, or equivalent) or Python/R visualization libraries
• Experience with Big Data tools (Spark/Hadoop) and handling large-scale data pipelines
• Exposure to cloud computing platforms (AWS, GCP, Azure) for data processing or storage
• Experience in deploying ML models / working in production environment
• Basic understanding of data engineering practices (ETL, data warehousing, pipelines)

Skills

• Python
• SQL
• Machine Learning
• Tableau
• AWS