Hudson Data

About Hudson Data

At Hudson Data, we view AI as both an art and a science. Our cross-functional teams — spanning business leaders, data scientists, and engineers — blend AI/ML and Big Data technologies to solve real-world business challenges. We harness predictive analytics to uncover new revenue opportunities, optimize operational efficiency, and enable data-driven transformation for our clients.

Beyond traditional AI/ML consulting, we actively collaborate with academic and industry partners to stay at the forefront of innovation. Alongside delivering projects for Fortune 500 clients, we also develop proprietary AI/ML products addressing diverse industry challenges.

Headquartered in New Delhi, India, with an office in New York, USA, Hudson Data operates globally, driving excellence in data science, analytics, and artificial intelligence.

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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. You’ll play a key role in transforming raw data into insights, building predictive models, and delivering data-driven strategies that have real business impact.

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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.

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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.

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Education & Certifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• Master’s 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 Certificate

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Why Join Hudson Data

At Hudson Data, you’ll 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.

About the Role

Hudson Data is looking for a Senior / Mid-Level SQL Engineer to design, build, optimize, and manage our data platforms. This role requires strong hands-on expertise in SQL, Google Cloud Platform (GCP), and Linux to support high-performance, scalable data solutions.

We are also hiring Python Programers / Software Developers / Front end and Back End Engineers

Key Responsibilities:

1.⁠Develop and optimize complex SQL queries, views, and stored procedures

• Build and maintain data pipelines and ETL workflows on GCP (e.g., BigQuery, Cloud SQL)
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• Manage database performance, monitoring, and troubleshooting
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• Work extensively in Linux environments for deployments and automation
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• Partner with data, product, and engineering teams on data initiatives

Required Skills & Qualifications

Must-Have Skills (Essential)

• Expert GCP mandatory
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• Strong Linux / shell scripting mandatory
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Nice to Have

• Experience with data warehousing and ETL frameworks
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• Python / scripting for automation
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• Performance tuning and query optimization experience

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.

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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. Youll have the opportunity to grow, experiment, and make a tangible impact in a culture that values creativity, precision, and collaboration.