Director of Data Science

Job Duties

• Lead a team of data science (DS) and machine learning (ML) experts to collaborate across the enterprise and solve AmeriLife’s most challenging data science and advanced analytics problems
• Manage a team of associates in varying locations and work arrangements
• Lead relationship with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
• Ability to formulate and execute recommendations based on insights provided by team members to drive optimization and improvement of sales development, revenue generation, marketing techniques, business strategies and outcomes
• Direct and manage small to large size projects
• Lead different functional teams to implement models and monitor outcomes
• Lead team to develop processes and tools to monitor and analyze advanced analytics model performance and data accuracy
• Strong problem-solving skills with an emphasis on implementation leadership
• Design and fine tune Generative AI Large Language Models (LLMs) to understand and build predictions or summaries from various data sources
• Work with Python, LLM/GenAI frameworks and tools AI/ML end-to-end solutions developing
• CI/CD pipelines development, LLM model containerizing and deployment on cloud or premise
• Collaborate with technology partners to adopt, design, build, and/or integrate MLOps tools for the organization, ensuring they support broad DS needs, and help other DS groups adopt modern MLOps practices
• Explore the advantages and limitations of privacy-preserving ML and synthetic data, to accelerate experimentation and better protect our customers’ data

Qualifications

Minimum Job Requirements

• 10+ years of progressive advanced analytics experience in a related field
• Demonstrated experience in hiring, retaining and scaling diverse, geographically dispersed, high-performing data scientists
• Advanced skills with statistical computer languages (Python, R, SLQ, etc.) to manipulate data and draw insights from data sets
• Broad knowledge of machine learning and statistics, with the ability to deep dive as well as converse at the executive level
• NLP/NLU and other deep learning experience a plus
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

Preferred Job Requirements

• Masters or PHD in Statistics, Mathematics, Computer Science or another quantitative field

Knowledge Skills, and Abilities

• Familiarity with and experience using the following software/tools:
  • Coding knowledge with several languages: C, C++, Java, JavaScript, etc.
  • Statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Databases and using statistical computer languages: R, Python, SLQ, etc.
  • Web services: Redshift, S3, Spark, DigitalOcean, etc.
  • Analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
  • Distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
  • Visualizing/presenting data for stakeholders using: Tableau, Power BI, ggplot, etc.
• Advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• A proven ability to drive business results with data-based insights derived from advanced analytics
• Comfortable working with and leading a range of stakeholders and functional teams
• The right candidate will have a passion for discovering solutions hidden in data sets and working with stakeholders to improve business outcomes
• Excellent written and verbal communication skills for coordinating across teams and exceptional experience/skills in managing/developing relationships with peer and senior level client executives