Data Scientist

Job Description: Must have skills - Data Scientist with: 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.

Job Description/ Details

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. #LI-CGTS #TS-3142