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Data Science Development Manager

Covenant Eyes
Full-time
Remote
United States






Overview






The Data Science Development Manager is responsible for leading a team of Data Scientists, Developers, and Ratings Specialists focusing on Data Science and Machine Learning. This role involves translating business needs into software solutions by working closely with internal and external stakeholders.

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The Data Science Development Manager works with emotionally taxing and ethically complex data and manages a team that requires a supportive leader who can recognize and address the psychological impacts these data sets may have on team members.

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Objectives

  • Champion and Improve Data Science understanding and use - collaborate with the Data Science team, management, and other departments to plan and execute projects that support organizational goals and enhance data-driven solutions.
  • Lead a Healthy Data Science Team in a high-trust fashion - manage a data science team to ensure they are engaged and performing effectively.Β  This includes setting objectives, organizing the work, motivation, communication measurement, training and development. Maintaining a healthy and resilient team environment by fostering empathy and support, ensuring psychological well-being and productivity. Creating a high-trust environment using Patrick Lencioni’s β€œFive Behavior Model” to maximize engagement and performance of the team.
  • Improve Operational Effectiveness - lead and guide the team in architectural and design decisions to develop and continuously improve the Data Science Pipeline, ensuring efficient transition of ML-powered applications from concept to production.








Responsibilities






  • Maintain understanding of the complex and intricate interactions of the design, ML, and development decisions, and contributes technically to the code base, AI/ML models and code, and technical design.
  • Identify trends and problems through complex data analysis on data from multiple sources that leads to software improvements that meet our members’ needs.
  • Turns data insights into a vision and requirements while building compelling narratives that communicate their importance to gain buy in and build alignment, with both internal and external partners.
  • Monitors the success of deployed models, software, and APIs to monitor service availability and improve outcomes for customers and the company.
  • Leads, mentors and/or works with an agile team of Engineers, Data Engineers, Data Scientists, Quality Assurance Engineers, and Data Ratings Specialists to remove impediments to development progress and to deliver software-based services to our customers based on business priorities as agreed to during release planning.
  • Communicates, coordinates, and collaborates effectively with many teams and departments across the business to ensure desired company outcomes from the service are achieved, stakeholders are informed, and to discover new opportunities for the service to contribute to company success.
  • Strives to keep informed on new leadership, management, financial, technical, people, and communication tools, in addition to new and current statistical methodologies and machine learning techniques.
  • Participates in leadership activities as requested including staff planning, recruiting, interviewing, hiring, performance evaluation, personnel management, manager training, stakeholder meetings, agile team meetings, and budgeting.
  • Develops and maintains a career development plan for all employees on their team.
  • Ensures each area of responsibility within his/her teams is documented and maintained for training and evaluation purposes.
  • Leads team by the standards set in place in the Employee Handbook.
  • Manages team attendance by reporting absences and ensuring responsibilities are covered when employees are absent.
  • Meets with assigned employees both individually and as a team on a consistent and regular basis.
  • Works cooperatively with the Director of Development to establish best practices/processes.








Qualifications






  • Possess a Bachelor’s in Statistics, Mathematics, Computer Science or another quantitative field and 5 years related work experience, or the equivalent without degree (9+ years’ experience).
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) as well as their real-world advantages/drawbacks.
  • Experience leading a team that leverages multiple machine learning and engineering frameworks and tools like: PyTorch, TensorFlow, Python, pandas, OpenCV, scikit-learn, MySQL, OracleDB, Git, and the modern software development lifecycle.
  • Domain expertise in at least one of the following areas: customer churn analysis, time series forecasting, computer vision, deep learning, recommender systems, segmentation, natural language processing or text analytics.A drive to learn and master new technologies and techniques.
  • Demonstrated excellence in planning, tracking, organizing and communicating complex and technical solutions with clarity and efficiency to diverse teams across the company.
  • Creative and strong problem-solving skills with a demonstrated ability to connect data science solutions to their human impact on our members.
  • Possess experience as a manager who has effectively led and motivated teams of technical professionals and understands the intricacies of software development.
  • Possess experience with agile development methodology and committed to improving the way we use the agile software development process.
  • Understand the dangers of the Internet and be committed to protecting our members and their families.
  • Most of your time will be spent at a desk using a phone, computer and monitor, and general office equipment. You may be required to reach with hands and arms; sit; stand; talk and hear; use your hands to finger, handle, or feel.

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Preferred:

  • 10+ years of experience manipulating data sets and building statistical models.
  • Has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field