Delve Deeper! Join one of Inc 5000’s fastest-growing companies as a Cloud Data Scientist. A top-rated Google Marketing Platform Partner, DELVE is your strategic partner for site-side analytics, campaign management, and advanced marketing science. In this role, you will join an energetic growing team of analysts, data engineers, and data scientists that drives client growth through a data-driven mindset that converts digital inefficiency into hard ROI.
This experienced mid-level position located in our Boulder, CO (or Minsk, Belarus) office will challenge you to deliver intelligent machine learning-driven marketing insights, predictions, and recommendations in a consultant-client settings. Using your creativity, technical programming skills, and passion for problem solving, you will develop and deploy cloud-based (mainly in Google Cloud Platform) data science solutions solving real world marketing business problems. The successful data scientist will be an independent self-starter comfortable with ambiguity and able to transform vague client business problems into tangible machine learning projects aimed at delivering measurable economic value.
You should exhibit an entrepreneurial spirit and enjoy tackling quantitative problems that most other people cannot solve (e.g., in your free time, you enter data mining competitions!). You are the kind of person that enjoys figuring out ways to use programming to automate manual tasks and optimize decision making. You also love “geeking out” and discussing different approaches and theories to solving problems with machine learning. You are curious and have a passion for knowledge discovery using data!
- Advanced level proficiency with Python (expertise in developing/deploying machine learning in R, Matlab, Octave, Java also considered)
- 2+ years creating data pipelines and developing/deploying machine learning models in a business setting (preferably using Python, but expertise in other languages will be
- Expertise in data cleansing, transformation, and model feature creation/abstraction/selection specifically for machine learning.
- Ability to discuss pros and cons of various structured and unstructured learning algorithms/methodologies (ANN vs. SVM, kMeans vs. SOM, Bagging vs. Boosting).
- Undergraduate degree in computer science, engineering, physics, math, economics, finance or other quantitative field (will consider in place of an undergraduate degree, a top 20% finish in any Kaggle.com competition awarding a cash prize).
- Passion for data storytelling and quantitative analysis (ability to provide at least one example of a research paper, blog post, or business presentation created within the past 2 years for school or work on topics of data science).
- Ability to communicate complex topics in simple terms.
- At least intermediate competency with any 2 of the following visualization/reporting tools: Excel, Tableau, QlikView, Looker, Power BI, Google Data Studio.
- Intermediate to advanced fluency in English.
- Exposure to cloud environments (Google Cloud Platform preferred but will consider exposure to Amazon Web Services and Microsoft Azure).
- Masters degree in computer science, engineering, physics, math, economics, finance or other quantitative field.
- Comfort with conveying complex ideas using abstract methods (e.g., mathematical equations, process maps, musical notation).
- Ability to provide personal Github repository with examples of problem solving code.
- At least one top 25% finish in a Kaggle.com competition (or other data science competition).
Please submit applications to email@example.com with:
1. A one-page description of the most interesting machine learning solution you have built.
2. 1-page resume attachment in PDF format.
Shortlisted applicants will be asked for the following before final round interviews:
3. transcripts from all degree-earning colleges/universities