Data Scientist

Who we are:
automotiveMastermind (aM) provides U.S. automotive dealers with software and marketing solutions to improve the efficiency of the vehicle sales process. The company’s cloud-based technology helps dealers more precisely predict automobile buying behavior and facilitates microtargeted customer communications to improve the efficiency of the sales process and strengthen customer retention.

automotiveMastermind (aM) delivers value to the market by…

• Predicting when existing consumers will be ready for their next vehicle based on a prior vehicle, sharpening the focus on high-potential targets
• Delivering a compelling offer to engage the customer and prompt a return to the participating dealership
• Connecting dealers to conquest opportunities
• Providing a platform to support dealer outreach and dialogue

aM was acquired by IHS Markit in 2017.  IHS Markit serves more than 50,000 key customers in more than 140 countries, including 80 percent of the Fortune Global 500. They help decision makers apply higher-level thinking to daily tasks and strategic issues across a host of industries and disciplines including energy, finance, automotive, engineering, technology, maritime and trade, aerospace and defense, chemical, economics and country risk.

What you will do:

Data Science is critical to aM’s core value proposition – the ability to predict consumer returns to market and understand key drivers behind timing and vehicle selection. The automotiveMastermind (aM) Data Science team is responsible for maintaining and enhancing existing models, creating new predictive capabilities, and partnering with the broader aM Data Strategy team to create data-driven solutions for a wide range of additional business problems.

Example outcomes of these efforts may include…

• Leveraging a variety of modeling techniques to create new or augmenting existing models
• Exploring new data assets, tools and techniques to strengthen results or create new predictive capabilities
• Performing ad hoc analysis or A/B testing to evaluate alternative methods or sources
• Creating new or derived variables to better capture relationships and improve model effectiveness
• Partnering with operations or commercial teams to apply data science capabilities to challenging business problems
• Identifying and analyzing additional data sources to bolster predictions and recommendations and collaborating with engineering to integrate new data sources and methods
• Creating scalable, decoupled, and extensible data science solutions via close collaboration with product, engineering and architecture
• Communicating data-driven insights and recommendations to non-technical stakeholders

Who you are:

• You possess 4+ years of related work experience in data analysis and machine learning (such as logistic regression, random forest, gradient boosting, deep learning) on large datasets, ideally in automotive-centric roles
• You are a skilled analyst, adept at not just answering the “what”, but, more importantly, the “why”
• You are comfortable working with large and complex datasets and are capable of sifting signal from noise
• You possess a Master of Science or PhD in a quantitative discipline (e.g., data science, economics, statistics, finance, operations research, computer science, mathematics, physics, electrical/mechanical/industrial engineering, etc.…) or a Bachelor of Science in a quantitative discipline and 6+ years of related work experience
• You are able to demonstrate mastery of the following:
  • Designing and building machine learning models using Python and/or R, SQL
  • The model building process – working with stakeholders to understand requirements, translating requirements into a clear understanding of what the model needs to do, capturing the right data and EDA, model selection including a broad, up-to-date understanding of the possibilities, testing, implementation, communicate results to stakeholders, and documentation.
  • Designing, implementing, troubleshooting pipelines in Cloud-based environments (GCP, AWS) and Airflow
  • Leveraging data visualization tools to share findings and and collect feedback on your analysis, monitor and communicate predictive model performance

What We Offer

• Competitive base salary, bonus plans and equity.
• A comprehensive, benefits package that includes medical, dental, vision and life insurance plans, paid time off, a generous 401k match with no vesting period, parental leave and 3 volunteering days each year. For more information on benefits, please access the benefits page on our careers site: https://careers.ihsmarkit.com/benefits.php.
• For work locations in the state of Colorado, the anticipated minimum base salary for this role would be $86,333. Compensation will be determined by the education, experience, knowledge, and abilities of the applicant.

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Equal Opportunity Employer:

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law.  Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. 

US Candidates Only:

The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law.



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