Data Analyst

About the Role

We are seeking a Data Analyst & Modeling Specialist with a passion for leveraging AI, machine learning, and cloud analytics to improve business processes, enhance decision-making, and drive innovation. Youll play a key role in transforming raw data into insights, building predictive models, and delivering data-driven strategies that have real business impact.

Key Responsibilities:

1. Data Collection & Management

2. Gather and integrate data from multiple sources including databases, APIs, spreadsheets, and cloud warehouses.

3. Design and maintain ETL pipelines ensuring data accuracy, scalability, and availability.
4. Utilize any major cloud platform (Google Cloud, AWS, or Azure) for data storage, processing, and analytics workflows.

5. Collaborate with engineering teams to define data governance, lineage, and security standards.

6. Data Cleaning & Preprocessing

7. Clean, transform, and organize large datasets using Python (pandas, NumPy) and SQL.

8. Handle missing data, duplicates, and outliers while ensuring consistency and quality.

9. Automate data preparation using Linux scripting, Airflow, or cloud-native schedulers.

10. Data Analysis & Insights

11. Perform exploratory data analysis (EDA) to identify key trends, correlations, and drivers.

12. Apply statistical techniques such as regression, time-series analysis, and hypothesis testing.
13. Use Excel (including pivot tables) and BI tools (Tableau, Power BI, Looker, or Google Data Studio) to develop insightful reports and dashboards.

14. Present findings and recommendations to cross-functional stakeholders in a clear and actionable manner

15. Predictive Modeling & Machine Learning

16. Build and optimize predictive and classification models using scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, and

17. Perform feature engineering, model tuning, and cross-validation for performance optimization.
18. Deploy and manage ML models using Vertex AI (GCP), AWS SageMaker, or Azure ML Studio.

19. Continuously monitor, evaluate, and retrain models to ensure business relevance.

20. Reporting & Visualization

21. Develop interactive dashboards and automated reports for performance tracking.

22. Use pivot tables, KPIs, and data visualizations to simplify complex analytical findings.

23. Communicate insights effectively through clear data storytelling.

24. Collaboration & Communication

25. Partner with business, engineering, and product teams to define analytical goals and success metrics.

26. Translate complex data and model results into actionable insights for decision-makers.

27. Advocate for data-driven culture and support data literacy across teams.

28. Continuous Improvement & Innovation

29. Stay current with emerging trends in AI, ML, data visualization, and cloud technologies.

30. Identify opportunities for process optimization, automation, and innovation.
31. Contribute to internal R&D and AI product development initiatives.

Required Skills & Qualifications

Technical Skills

• Programming: Proficient in Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, ).
• Databases & Querying: Advanced SQL skills; experience with BigQuery, Redshift, or Azure Synapse is a plus.
• Cloud Expertise: Hands-on experience with one or more major platforms Google Cloud, AWS, or Azure.
• Visualization & Reporting: Skilled in Tableau, Power BI, Looker, or Excel (pivot tables, data modeling).
• Data Engineering: Familiarity with ETL tools (Airflow, dbt, or similar).
• Operating Systems: Strong proficiency with Linux/Unix for scripting and automation.

Soft Skills

• Strong analytical, problem-solving, and critical-thinking abilities.
• Excellent communication and presentation skills, including data storytelling.
• Curiosity and creativity in exploring and interpreting data.
• Collaborative mindset, capable of working in cross-functional and fast-paced environments.

Education & Certifications

• Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• Masters degree in Data Analytics, Machine Learning, or Business Intelligence preferred.

• Relevant certifications are highly valued:

• Google Cloud Professional Data Engineer

• AWS Certified Data Analytics – Specialty

• Microsoft Certified: Azure Data Scientist Associate

• TensorFlow Developer Certifications

Why Join Hudson Data

At Hudson Data, youll be part of a dynamic, innovative, and globally connected team that uses cutting-edge tools from AI and ML frameworks to cloud-based analytics platforms to solve meaningful problems. You'll have the opportunity to grow, experiment, and make a tangible impact in a culture that values creativity, precision, and collaboration.