Digible, Inc. is an emerging startup in the digital marketing and technology field. We bring the industry's most advanced digital strategies, products and research to scale. Our focus is multifamily marketing and student housing with a client base spanning across 50 markets. Digible has big plans for expansion in 2019 for both our agency and SAAS platform. We are energetically pursuing top talent in the Denver area to grow our team and help craft the company’s future.

Digible, Inc. is looking for an experienced Data Scientist to mine data, develop/test/train/tune machine learning models, conduct exploratory analysis, and build data visualization. The Data Scientist will work with our Data Engineer to scale, deploy, and productionize machine learning algorithms. This role will play an integral part in Digible’s roadmap, and will report to the Chief Data Officer.

Primary Responsibilities:

• Assist Data Engineer in early stages to evolve our infrastructure and data pipelines
• Further develop and tune existing mathematical and statistical models, while prototyping and training other ML product features
• Leverage data mining algorithms to manage and prepare data for modeling
• Lead A/B & multi-variate test & learn, and optimization measurement efforts
• Conduct exploratory and ad hoc analysis
• Assist with the development of business intelligence solutions including both external products and internal data enablement and analytics
• Identify, acquire, and assess new data sources to improve and extend data science solutions
• Partner with Data Engineer and Software Engineering team to deploy machine learning algorithms with distributed systems frameworks into production

Qualifications:

• Bachelor Degree in Mathematics, Statistics, Operation Research or a related discipline or equivalent business experience in machine learning and data science
• A Master’s Degree is preferred
• 3+ years of advanced Python and SQL experience
• 3+ years of experience with analysis, data science, and predictive modeling
• 3+ years of conducting exploratory analysis including the use of data visualization tools
• Work experience in an AdTech or Martech company is preferred
• Nice to have - some experience with data pipelines and engineering including distributed cluster computing frameworks

Knowledge and Skills:

• Capable of working with large data sets including cleaning, parsing, and analyzing
• Advanced competency and experience with data mining, machine learning, and statistical models including linear and logistic regression, time series, clustering, PCA, Markov, decision trees, support vector machine, multiple kernel imputation, and neural networks.
  • Particular use of ML packages such as Pytorch, Scikit-learn, and/or XGBoast
• Experience with BI tools such as Periscope, Scisense, Tableau, Looker, D3, etc.

• Able to demonstrate advanced computer and analytical skills with a knack for uncovering patterns and actionable insights out of data
• Familiar with the following RDBMS, cloud storage & computing, and ML engineering tools:
  • PostgreSQL and MS SQL
  • S3, Snowflake, and/or Redshift, Google BigQuery, Hive
  • Apache Spark, Databricks, and/or Hadoop, MapReduce
• Experience and understanding of web data including ad server logs, click stream, cookie pools, UID’s, UTM, Floodlight, and Google Analytics
• Nice to have – experience with API’s to build real-time data pipelines
• Kanban or Scrum experience
• Familiarity with CI/CD and experience with Github
• Strong curiosity, creative thinker and desire to design build and automate
• Strong business acumen with the ability to frame a problem statement, hypothesis, and deliver insights valuable to the business
• Ability to explain complex technical problems to broad audiences
• Ability to work well independently in a fast-paced environment
• Comfortable in startup environment including wearing various hats
• Ability to multi task, prioritize and get things done
• An aptitude for seeing the big picture and possessing an entrepreneurial spirit

Compensation:

• Competitive salary
• Stock options in the form of equity
• Full benefits
• 401k match
• Flexible work schedule with the ability to work remote 2 days/week