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

• Gather and integrate data from multiple sources including databases, APIs, spreadsheets, and cloud warehouses.
• Design and maintain ETL pipelines ensuring data accuracy, scalability, and availability.
• Utilize any major cloud platform (Google Cloud, AWS, or Azure) for data storage, processing, and analytics workflows.
• Collaborate with engineering teams to define data governance, lineage, and security standards.

2. Data Cleaning & Preprocessing

• Clean, transform, and organize large datasets using Python (pandas, NumPy) and SQL.
• Handle missing data, duplicates, and outliers while ensuring consistency and quality.
• Automate data preparation using Linux scripting, Airflow, or cloud-native schedulers.

3. Data Analysis & Insights

• Perform exploratory data analysis (EDA) to identify key trends, correlations, and drivers.
• Apply statistical techniques such as regression, time-series analysis, and hypothesis testing.
• Use Excel (including pivot tables) and BI tools (Tableau, Power BI, Looker, or Google Data Studio) to develop insightful reports and dashboards.
• Present findings and recommendations to cross-functional stakeholders in a clear and actionable manner

4. Predictive Modeling & Machine Learning

• Build and optimize predictive and classification models using scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, and H2O.ai.
• Perform feature engineering, model tuning, and cross-validation for performance optimization.
• Deploy and manage ML models using Vertex AI (GCP), AWS SageMaker, or Azure ML Studio.
• Continuously monitor, evaluate, and retrain models to ensure business relevance.

5. Reporting & Visualization

• Develop interactive dashboards and automated reports for performance tracking.
• Use pivot tables, KPIs, and data visualizations to simplify complex analytical findings.
• Communicate insights effectively through clear data storytelling.

6. Collaboration & Communication

• Partner with business, engineering, and product teams to define analytical goals and success metrics.
• Translate complex data and model results into actionable insights for decision-makers.
• Advocate for data-driven culture and support data literacy across teams.

7. Continuous Improvement & Innovation

• Stay current with emerging trends in AI, ML, data visualization, and cloud technologies.
• Identify opportunities for process optimization, automation, and innovation.
• 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, H2O.ai).
• 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.