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Full-Time

Head of Data Science & Machine Learning

Posted on 6/27/2024

Niche

Niche

501-1,000 employees

Provides rankings and profiles for U.S. institutions

Data & Analytics
Education

Compensation Overview

$188.4k - $235.5kAnnually

+ Annual Bonus + Stock Option Program

Expert

Remote in USA

Category
Applied Machine Learning
Data Management
Data Science
AI & Machine Learning
Data & Analytics
Required Skills
Microsoft Azure
Python
Data Science
Tensorflow
R
Data Structures & Algorithms
Pytorch
SQL
AWS
Snowflake
Requirements
  • Advanced degree (Ph.D. or Master's) in computer science, statistics, mathematics, or a related quantitative field
  • Minimum of 10 years of experience in data science, with at least 5 years in a leadership role
  • Extensive experience in data science, with a proven track record of leading successful data science projects ideally in the SaaS, B2C, or two-sided marketplace sector
  • Expert knowledge of machine learning algorithms, data modeling, and statistical analysis
  • Strong leadership skills with the ability to build, manage, and mentor a team of data scientists
  • Hands-on experience with programming languages commonly used in data science and ML, such as Python, R, and SQL, along with experience working with libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn
  • Experience working with cloud data science and ML platforms (e.g., AWS SageMaker, Azure ML, Snowflake, Databrick, etc.)
  • Excellent communication and stakeholder management skills, with the ability to translate technical concepts into business insights and recommendations
  • Ability to think strategically and drive innovation with a strong focus on execution and a commitment to staying at the forefront of data science trends
Responsibilities
  • Conduct a thorough assessment of the current data science and ML infrastructure and capabilities
  • Understand current challenges and identify immediate opportunities for leveraging data science and ML to enhance customer experience and business operations
  • Develop relationships with key stakeholders to align on objectives and expectations
  • Identify and implement quick wins to demonstrate the value and opportunities of data science and ML
  • Develop and communicate a clear vision and strategy for data science and ML within the company
  • Partner with stakeholders and data product manager to develop a comprehensive roadmap for data science and ML capabilities that reflects the strategic vision and business priorities
  • Begin development work of the data science and ML roadmap and deliver quick wins
  • Work with the head of data engineering to identify infrastructure and platform needs that enable efficient development and productionization of data science and ML models
  • Mentor and coach others within the larger data organization
  • Complete development and deploy initial models into production to optimize customer experience and customer retention
  • Assess and refine the performance of these models based on data insights and stakeholder feedback
  • Collaborate with product and engineering teams to integrate AI-driven features and functionalities into products and services
  • Formalize the vision of the data science and ML organization along with resource needs based on the initial wins, learning, and strategic priorities
  • Start building the data science and ML team by recruiting and onboarding key talents fostering a culture of continuous learning, high performance, collaboration, and excellence
  • Achieve significant progress in delivering the planned roadmap and demonstrate the impact on business outcomes
  • Partner with senior leadership and cross-functional teams to identify and advocate potential opportunities for leveraging data science and AI
  • Stay abreast of the latest developments and innovations in data science, ML, and AI through industry partnership and outreach and establish thought leadership through publication and presentation

The company offers comprehensive rankings and profiles for educational institutions, neighborhoods, and employers in the U.S., leveraging data analysis, public data sets, and user reviews to provide detailed insights for decision-making.

Company Stage

Series C

Total Funding

$44.8M

Headquarters

Pittsburgh, Pennsylvania

Founded

2002

Growth & Insights
Headcount

6 month growth

-1%

1 year growth

5%

2 year growth

47%