Senior Data Scientist

Responsibilities

• Lead end-to-end analytics and ML solutions
• Own problem framing, data exploration, feature engineering, model development, validation, and deployment
• Deliver scalable solutions in Snowflake / cloud environments aligned with enterprise standards
• Drive data quality and customer/entity resolution initiatives
• Design and implement approaches for customer de-duplication, entity resolution, and master data improvement
• Partner with upstream/downstream teams to improve data accuracy, consistency, and usability
• Develop and operationalize machine learning capabilities
• Apply NLP, entity matching, and advanced analytics techniques to improve business processes
• Move models from experimentation to production-grade pipelines with monitoring and performance tracking
• Translate analytics into business impact
• Collaborate with product owners, stakeholders, and leadership to define use cases and success metrics
• Present insights in a clear, outcome-focused manner to drive adoption and decision-making
• Mentor and elevate team capabilities
• Provide technical guidance to junior team members within Sulguni
• Promote best practices in coding, data modeling, and experimentation
• Continuously improve tools, methods, and scalability
• Research and implement improvements in algorithms, data models, and processing approaches
• Optimize performance, cost, and reliability of data and ML pipelines

• Business & Applied Statistics – Working to Advanced Knowledge
• Applies statistical methods to real-world business problems (e.g., entity resolution confidence scoring, model evaluation)
• Interprets results and translates findings into actionable recommendations
• Identifies data biases, sampling issues, and potential misinterpretations
• Accuracy & Data Quality – Extensive Experience
• Champions high-quality, production-grade data solutions
• Designs validation frameworks, automated checks, and monitoring for pipelines
• Balances speed and accuracy in fast-moving delivery environments
• Drives improvements in enterprise data quality standards and practices
• Analytical Thinking – Advanced Knowledge
• Breaks down ambiguous, complex problems into structured analytical approaches
• Identifies root causes in data inconsistencies, customer duplication, and system gaps
• Evaluates multiple solution paths, balancing business impact, scalability, and effort
• Synthesizes insights into clear recommendations for leadership
• Top Candidate Will Have:
  Machine Learning & AI – Advanced Knowledge
• Develops and deploys machine learning models (e.g., clustering, classification, entity resolution, NLP)
• Applies Python-based ML ecosystems (e.g., pandas, scikit-learn, NLP libraries)
• Designs experiments, evaluates model performance, and iterates based on results
• Understands tradeoffs between model complexity, interpretability, and scalability
• Programming & Software Practices – Advanced Working Knowledge
• Writes clean, efficient, and production-ready code (primarily Python, SQL)
• Implement version control, testing, and modular design principles
• Contributes to shared codebases and reusable components
• Query & Data Engineering (SQL / Snowflake) – Extensive Experience
• Designs and optimizes complex queries across large-scale, distributed datasets
• Builds performant data pipelines, transformations, and aggregation layers
• Applies advanced SQL (window functions, CTEs, multi-source joins)
• Optimizes cost and performance in cloud data platforms (Snowflake)