Senior Data Scientist (Machine Learning)

Recruiter
SquarePeg
Location
San Francisco
Salary
Competitive
Posted
29 Apr 2022
Closes
18 May 2022
Employer Sector
Technology, ICT & Telecoms
Contract Type
Permanent
Hours
Full Time
Travel
None

Job Overview

At Dynam.AI, we're looking for a Senior Data Scientist to become a core member of our analytics team. The ideal candidate will help unlock the full power of our data by building and enhancing our statistical and machine learning modeling capabilities to influence various parts of the customer lifecycle, including lead management, customer acquisition, retention, upsell, and engagement. Fueled by data and the desire to connect the dots differently, our highly skilled and collaborative teams drive our platform. We make it easy for growth-oriented companies to expand their reach with our fully-managed, end-to-end solutions from proprietary technology to marketing and infrastructure services.

Responsibilities

  • Quickly gain a deep understanding of our data, including data sources, architecture, and systems.
  • You'll use foundational data science methodologies to identify relationships/drivers of critical metrics related to marketing objectives.
  • Create a framework for model development that will help select the correct model/technique for the right business problem, including predictive and explanatory models.
  • You'll identify areas of opportunities for model improvement and conduct periodic performance reads.
  • Develop both real-time and batch machine learning models
  • Apply advanced visualization methods to provide critical insights from models and share those with our leadership team.
  • Keep on top of the latest trends in the industry to research and apply new analytical methods.
  • Provide input and set boundary constraints for the machine learning infrastructure to scale our products.
  • Anticipates future business needs and identifies opportunities for complex analysis
  • Gathers and analyzes data to solve and address highly complex business problems and evaluate scenarios to make predictions on future outcomes and support decision making
  • Design and drive the creation of new standards and best practices in statistical data modeling, big data, and optimization tools.
  • Realize solutions to business problems using data analysis, data mining, optimization tools, and machine learning/deep learning techniques and statistics
  • Deploy data-science and technology-based algorithmic solutions to address business needs
  • Produce large-scale implementations of Linear, Non-Linear and Generalized Linear models and their extensions, including Hierarchical and Bayesian variants; Survival models; Spatial and Time-series models; Machine Learning algorithms such as Neural Networks; Support Vector Machines, and so on.

Qualifications

  • Ph.D. or M.S. in Computer Science, Math, Statistics, Physics, Economics, or related quantitative field.
  • 3+ years of experience deploying algorithms in a production environment
  • Both theoretical and applied knowledge of machine learning and AI.
  • Experience designing algorithms for a relevance system such as forecasting, search, personalization, etc.
  • Advanced proficiency in Python, PyTorch, and Tensorflow.
  • Background in biophysics, neuroscience, engineering, computer science, mathematics, chemistry, bioinformatics, or related STEM fields.
  • Deep understanding of mathematical principles of science and engineering, including signal processing, experimental design, data analysis, and statistics.
  • Experience in startups, rapid prototyping, and innovating in a small dynamic group.
  • Bachelor's degree or higher in physics or a related STEM field.
  • Proven experience in machine learning.
  • Proven experience in data science statistical data analysis.
  • Proven experience working with client data (not coursework).
  • Experience with image and data pipelines.
  • Experience with cloud and web APIs.
  • Experience with Agile R&D, Scrum, and/or Kanban.
  • Experience with databases, data analysis, large datasets.
  • Experience with edge deployment and computing.
  • Experience with virtualization and orchestration software.
  • Experience with CI/CD.