- 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
Requirements
- 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, NumPy, 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 MicroStrategy
- Familiarity with cloud data platforms, distributed data-processing environments, or production analytics workflows
Core Competencies
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.
Highest-signal resume keywords
- Data Analysis
- Statistical Modeling
- Python Programming
- SQL Proficiency
- Machine Learning
ATS Optimization Keywords
Hard Skills
- Data Science
- Statistical Methods
- Model Evaluation
- Data Cleaning
- Data Transformation
- Pattern Identification
- Hypothesis Testing
- Analytical Problem-Solving
- Data Visualization
- Cloud-Based AI Services
Soft Skills
- Strong Communication Skills
Industry Keywords
- Data Warehousing
- Data Processing Workflows
- Distributed Data Processing
- Business Use Cases
- Analytics Capabilities
Tools & Technologies
- Pandas
- NumPy
- Scikit-Learn
- Power BI
- Tableau
- MicroStrategy
- AI Tools
- Machine Learning Frameworks