Marketing Data Scientist

Desired Skills and Experience Experience Range : 4+ Years

NP : Immediate to 15 Days

Skills : Data Science, Python, Model Buidling, Azure ML

Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our solutions, our 3900+ tribe is solving problems that eventually impact the lives of millions globally. Headquartered in Silicon Valley, you'll find our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and Singapore, including a substantial remote global workforce.

Working at Tiger Analytics, you'll be at the heart of an AI revolution. Experienced Data Scientist with a strong background in Microsoft Fabric and related Azure technologies, capable of transforming raw data into actionable insights. The ideal candidate will possess advanced skills in data science, feature engineering, machine learning model development, and data engineering , with hands-on expertise in Azure Machine Learning , Spark , and Python . In addition to technical expertise, the candidate should bring domain knowledge in wealth management marketing data to ensure that analytics and models align with industry-specific requirements.

Ingest, clean, and analyze raw structured and unstructured datasets within Microsoft Fabric and One Lake environments.

Perform feature engineering , data enrichment, and transformation to prepare datasets for modeling.

Design, build, and deploy machine learning models in Fabric Data Science , Azure Machine Learning for predictive analytics, prospect identification, targeting, segmentation, personalization, campaign performance and other business use cases.

Implement end-to-end data pipelines using Fabric Data Engineering and Spark , ensuring scalability and performance optimization.

Write high-quality Python code for data preprocessing, model training, evaluation, and automation workflows.

Apply statistical analysis and data visualization techniques to generate insights and communicate findings effectively to business stakeholders.

Collaborate with cross-functional teams including Marketing, Business Intelligence, and IT to align solutions with business objectives in the wealth management domain .

to support targeted outreach and performance measurement.

Ensure compliance with data governance, privacy, and regulatory requirements in financial services analytics.

Required Skills & Experience:

Strong hands-on experience with Microsoft Fabric Data Science and Data Engineering workflows.

Proven expertise in data analysis , cleaning, and preprocessing of large-scale datasets.

Solid track record in feature engineering and building machine learning models for production.

Hands-on experience in Azure Machine Learning environment, including pipelines, model deployment, data drift, model drift and monitoring.

Proficiency in Spark for distributed data processing and Python for advanced analytics and automation.

Working knowledge of SQL for data querying and manipulation.

Exposure to marketing data from the wealth management domain, including customer lifecycle analytics, segmentation, and campaign performance .

Familiarity with RAG (Retrieval-Augmented Generation) , AI-powered personalization, or recommendation systems.

Knowledge of predictive audience modeling or conversion prediction in financial services.

Every individual comes with a different set of skills and qualities so even if you don't tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.

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