Data Scientist

• Analyze structured and unstructured datasets to identify trends and answer business questions
• Develop, test, and refine statistical and analytical models
• Contribute to analytics capabilities aligned with product roadmaps, customer needs, and business use cases
• Partner with data warehouse engineers, data engineers, product teams, subject-matter experts, and stakeholders on end-to-end analytical solutions
• Prepare, clean, transform, and validate data for analysis, modeling, reporting, and experimentation
• Evaluate new data sources and analytical methods
• Document analytical approaches and communicate findings
• Support deployment and ongoing improvement of data science solutions

• 2–4 years’ experience in data science, analytics, statistical modeling, or a related field, including relevant internships, academic projects, or applied professional experience
• Working knowledge of Python and SQL
• Understanding of statistical methods, model evaluation, and analytical problem-solving
• Experience identifying patterns, testing hypotheses, and communicating actionable findings from datasets
• Familiarity with database concepts, data warehousing, or data-processing workflows
• Strong written and verbal communication skills
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field, or equivalent practical experience
• Coursework, academic projects, certifications, or early professional experience involving artificial intelligence, machine learning, or generative AI
• Experience with pandas, Num Py, scikit-learn, or similar analytical tools
• Exposure to AI or machine-learning tools, frameworks, APIs, or cloud-based AI services
• Experience applying AI or machine learning to practical business, product, or customer use cases
• Exposure to R or other data science and statistical tools
• Experience with Power BI, Tableau, or Micro Strategy
• Familiarity with cloud data platforms, distributed data-processing environments, or production analytics workflows

Demonstrates expertise in data analysis, statistical modeling, and machine learning, with proficiency in Python and SQL. Capable of collaborating with cross-functional teams to develop and implement data-driven solutions that address business needs.

• Data Analysis
• Statistical Modeling
• Python Programming
• SQL Proficiency
• Machine Learning

• Data Science
• Statistical Methods
• Model Evaluation
• Data Cleaning
• Data Transformation
• Pattern Identification
• Hypothesis Testing
• Analytical Problem-Solving
• Data Visualization
• Cloud-Based AI Services

• Strong Communication Skills

• Data Warehousing
• Data Processing Workflows
• Distributed Data Processing
• Business Use Cases
• Analytics Capabilities

• Pandas
• Num Py
• Scikit-Learn
• Power BI
• Tableau
• Micro Strategy
• AI Tools
• Machine Learning Frameworks