Data Scientist

• Excellent storytelling & communication:
  Experience working with both business users and technical audience. Able to translate complex concepts in ways easy to understand.
• Expert Python is the most key technical skill.
• Machine Learning (ML) models, and LLMs.
• Visualization (Examples: Plotly or any other).
• Worked with large data sets, statistical methods, models in production.
• AWS exposure.
• Statistics.
• Advanced SQL.

Nice to have:

• Super beneficial/nice to have:
  GenAI, Graph DBs or algorithms.
• Financial / regulated industries.
• We are seeking an experienced Senior 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.