Lead Data Scientist - Finance Analytics

As a Lead Data Scientist joining the Finance Analytics team at our company, you will be responsible for analyzing financial data to generate insights, recognize patterns, and propose automation opportunities within finance and accounting functions. Your expertise in data engineering and advanced analytics will play a crucial role in converting raw financial data into valuable insights. Collaboration with finance teams to understand business requirements will be essential. **Key Responsibilities:** - Apply advanced analytics techniques to derive insights from financial data sets - Build and optimize data pipelines using Python, Spark, and SQL for data preparation - Develop machine learning models to identify patterns, anomalies, and automation opportunities - Create interactive dashboards and visualizations using BI tools for effective communication of insights - Collaborate with finance teams to translate data needs into analytical solutions - Identify and track relevant metrics to provide meaningful business intelligence - Conduct exploratory data analysis to discover trends and relationships in financial data - Mentor junior data scientists on analytical techniques and best practices - Implement statistical analysis methods to validate findings and ensure data quality - Document methodologies, processes, and results for reproducibility and knowledge sharing **Qualifications Required:** - 5-7 years of experience in data science or analytics, with exposure to financial or business data - Strong technical background in data engineering and pipeline development - Advanced proficiency in Python, experience with Spark for large-scale data processing - Proficiency in SQL for data extraction and manipulation - Experience in building dashboards and visualizations using BI tools (Power BI, Tableau, Looker, etc.) - Ability to communicate technical concepts to non-technical stakeholders - Understanding of basic financial concepts and metrics - Bachelor's degree in computer science, Data Science, Statistics, or related technical field If you possess the below additional qualifications, we would be excited to see it in your profile: - Experience working in cross-functional teams in fast-paced environments - Familiarity with agile methodologies and collaborative development practices - Experience with version control systems (Git) and collaborative coding - Knowledge of cloud computing platforms (AWS, Azure, GCP) - Understanding of data governance and data quality best practices - Curiosity and a willingness to learn about finance and accounting concepts - Creativity in presenting data insights through effective visualizations - Continuous learning mindset to stay updated with emerging technologies and techniques in data science If you find this opportunity intriguing, we invite you to apply by submitting your CV and a cover letter showcasing why you are the perfect fit for this role. Signant Health is dedicated to celebrating and supporting differences within our workplace and is committed to equal employment opportunity for all individuals. As a Lead Data Scientist joining the Finance Analytics team at our company, you will be responsible for analyzing financial data to generate insights, recognize patterns, and propose automation opportunities within finance and accounting functions. Your expertise in data engineering and advanced analytics will play a crucial role in converting raw financial data into valuable insights. Collaboration with finance teams to understand business requirements will be essential. **Key Responsibilities:** - Apply advanced analytics techniques to derive insights from financial data sets - Build and optimize data pipelines using Python, Spark, and SQL for data preparation - Develop machine learning models to identify patterns, anomalies, and automation opportunities - Create interactive dashboards and visualizations using BI tools for effective communication of insights - Collaborate with finance teams to translate data needs into analytical solutions - Identify and track relevant metrics to provide meaningful business intelligence - Conduct exploratory data analysis to discover trends and relationships in financial data - Mentor junior data scientists on analytical techniques and best practices - Implement statistical analysis methods to validate findings and ensure data quality - Document methodologies, processes, and results for reproducibility and knowledge sharing **Qualifications Required:** - 5-7 years of experience in data science or analytics, with exposure to financial or business data - Strong technical background in data engineering and pipeline development - Advanced proficiency in Python, experience with Spark for large-scale data processing - Proficiency in SQL for data extraction and manipulation - Experience in building dashboards and visualizations using BI tools (Power BI, Tableau, Looker, etc.) - Ability to communicate technical concepts to non-technical stakeholder