Principal AI-ML Data Scientist

$150,000 - $180,000 yearly
  • The Resume Review - Recruiting Department
  • Remote (Nashville, TN, USA)
  • May 25, 2021
Full time Information Technology Research

Job Description

Job description
Job Duties:
  • Builds and validates predictive models of high risk/reward or ambiguous problems with no initial solution utilizing large scale data from multiple data sources and serves and the expert in formulating solutions using Artificial Intelligence, Machine Learning and Deep Learning.  Ensures adoption of the model and reviews other Data Scientists' models.
  • Serves as a thought leader and strategic partner to cross functional leaders promoting and educating the business on appropriate application for AI, ML and DL.
  • Uses machine learning and other appropriate techniques to create data-driven solutions for various business use-cases
  • Solves complex, strategic issues using data science methodologies across multiple business units or domains. Leads projects with external partners to develop a minimal viable product to meet those needs while resolving any issues that may arise.
  • Leads the analysis and mining of very large quantities of data with expertise in several domains to find patterns and insights utilizing statistical software
  • Adept with project management principles.
  • Writes Python code in on prem or cloud solutions within Bridgestone’s environment.
  • Leads the development AI-ML standards and processes for the department.
  • Contributes to the organization's data strategy and influences the data roadmap. Leads the efforts to find new data sources or leveraging existing data sources and works with business partners to bring them into the data stack. 
  • Interprets, communicates, and presents analytic results to C-Level executives and below
  • Consistently collaborates with fellow data scientists and frequently interacts with business partners, project managers, cross-functional teams, key stakeholders, and other domains to generate ideas/hypotheses, test hypotheses, build analytics capabilities and drive business value.
  • Mentors and assists in technically supervising less experienced Data Scientists. Guides the formulation of individual development plans for the Data Scientists. Leads best practice sharing opportunities and knowledge of industry trends and innovations in AI and ML.
  • Analyzing D&A ecosystem to highlight areas for growth and M&A opportunities.
Required Qualifications:
  • PhD degree in a quantitative field including but not limited to data science, physics, computer science, math, engineering, and statistics and 7+ years of data science experience (Or Master’s Degree with 10+ years’ experience).
  • Expertise in Machine Learning in auto or related industries (incl. image, speech, pattern recognition & anomaly detection) – SciKit-Learn, TensorFlow or PyTorch, Pandas, NumPy
  • Expertise (5+ years) operating and deploying models in cloud environments e.g., AWS, Azure, collaborating with IT, Data Engineers, ML Engineers.
  • Experience with distributed computing (Spark/MLLib)
  • Experience in software development processes including Dev/QA/prod, release cycles, Continuous Improvement/ Continuous Development, source control, code reviews etc.
  • Experience in IoT and streaming data analytics
  • Able to work with large data sets from multiple data sources (text, speech, images, structured, unstructured).
  • 10 years of programming experience in statistical software (for example Python, R, or SAS) and able to demonstrate proficiency at an expert level. At least 7 years’ experience with Python.
  • Experience working in large and complex projects using common project management methodologies e.g., Agile, Waterfall, Six Sigma, Lean
  • Able to build or support the building of business cases related to data science related projects.
  • Enjoys working collaboratively with other data scientists and multiple stakeholders across the business unit and with external partners.
  • Adept at effectively solving complex problems by breaking them down into logical steps and communicating results in a concise way to Senior Executives and able to defend/debate the results of the analyses.
  • Intellectual curiosity, a passion for data and a results orientation.
  • Enjoys mentoring, training and coaching other data scientists and analysts