About the Role
We are seeking an experienced Data Scientist to join our team and drive impactful data-driven insights that inform strategic business decisions. This role requires a blend of technical expertise, analytical rigor, and excellent communication skills to collaborate effectively across technical and non-technical stakeholders.
Key Responsibilities
Design, develop, and deploy machine learning models to solve complex business problems
Explore and implement generative AI solutions to enhance analytical capabilities and business processes
Create advanced, interactive visualizations and dashboards to communicate insights to diverse audiences
Collaborate with cross-functional teams to understand business needs and translate them into analytical solutions
Conduct rigorous statistical analyses to validate findings and ensure data integrity
Lead stakeholder engagement, presenting complex technical concepts in accessible ways
Mentor junior team members and contribute to the growth of the data science practice
Deploy and maintain models in cloud-based environments
Drive end-to-end project delivery from problem definition through implementation
Required Qualifications
Python Proficiency: Expert-level skills in Python for data analysis, modeling, and automation (required)
Data Manipulation & Processing: Strong proficiency in pandas for data analysis and PySpark for large-scale distributed data processing
SQL: Advanced SQL skills for data extraction, transformation, and analysis across various database systems
Statistics: Strong foundation in statistical methods, experimental design, and hypothesis testing (required)
Machine Learning: Hands-on experience building, training, and deploying ML models in production environments
Advanced Visualization: Proficiency with Plotly and Plotly Dash for creating interactive, production-grade visualizations
Cloud Technologies: Experience with cloud platforms (AWS, Azure, or GCP) for data processing and model deployment
Communication Skills: Exceptional ability to communicate technical findings to both technical and non-technical audiences
Stakeholder Management: Proven track record of managing stakeholder relationships and driving alignment
Education: Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related quantitative field; advanced degree (Master's or PhD) preferred
Preferred Qualifications
Generative AI: Experience with large language models (LLMs), prompt engineering, and GenAI applications
Experience with graph databases and graph analytics
Knowledge of network analysis and graph-based algorithms
Experience in financial services or regulated industries
Familiarity with MLOps and model monitoring best practices

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