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GitHubAbout 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.
Shubham Vishwakarma
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Full Stack Developer - Averlon