As a Lead Data Scientist at Signant Health, you will play a crucial role in the Finance Analytics team by analyzing financial data to drive insights, identify patterns, and recommend automation opportunities within finance and accounting functions. Your expertise in data engineering and advanced analytics will be instrumental in transforming raw financial data into meaningful insights and collaborating with finance teams to address business needs effectively. **Key Responsibilities:**
Apply advanced analytics techniques to extract insights from financial data sets
Build and optimize data pipelines using Python, Spark, and SQL for data preparation
Develop and implement 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 understand data needs and provide analytical solutions
Identify and track relevant metrics to support data-driven decision making
Conduct exploratory data analysis to uncover trends and relationships
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 and experience with Spark for large-scale data processing
Experience working with data from Snowflake Data Lake or similar cloud-based data platforms
Proficiency in SQL for data extraction and manipulation
Experience applying machine learning algorithms to solve business problems
Ability to communicate technical concepts to non-technical stakeholders
Understanding of basic financial concepts and metrics
Strong problem-solving skills and attention to detail
Bachelor's degree in computer science, Data Science, Statistics, or related technical field
The company offers a variety of perks and benefits including Medical Insurance, Group Accidental Coverage/Insurance, Group Term Life Insurance, Company Paid Subscription to Calm, Employee Referral Program, Wellness Program, Proof! Employee Recognition Program, and Burn Along Digital fitness and wellness platform. If you are someone who thrives in a fast-paced environment, has a continuous learning mindset, and is willing to explore and contribute to the Finance Analytics team at Signant Health, we encourage you to apply by submitting your CV and a cover letter demonstrating why you are a perfect fit for this role. As a Lead Data Scientist at Signant Health, you will play a crucial role in the Finance Analytics team by analyzing financial data to drive insights, identify patterns, and recommend automation opportunities within finance and accounting functions. Your expertise in data engineering and advanced analytics will be instrumental in transforming raw financial data into meaningful insights and collaborating with finance teams to address business needs effectively. **Key Responsibilities:**
Apply advanced analytics techniques to extract insights from financial data sets
Build and optimize data pipelines using Python, Spark, and SQL for data preparation
Develop and implement 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 understand data needs and provide analytical solutions
Identify and track relevant metrics to support data-driven decision making
Conduct exploratory data analysis to uncover trends and relationships
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 and experience with Spark for large-scale data processing
Experience working with data from Snowflake Data Lake or similar cloud-based data platforms
Proficiency in SQL for data extraction and manipulation
Experience applying machine learning algorithms to solve business problems
Ability to communicate technical concepts to non-technical stakeholders
Understanding of basic financial concepts and metrics
Strong problem-solving skills and attention to detail
Bachelor's degree in computer science, Data Science, Statistics, or related technical field
