Data Scientist

Data Scientist

Archetype’s Analytic Insights consulting practice develops insights for our customers through innovative technology solutions. Archetype sees the value in data science and self-service analytics, providing these capabilities to our customers. At Archetype, you will get to work with the best of breed products that include Snowflake, Fivetran, dbt, Tableau, ThoughtSpot, Dataiku, DataRobot and partner with our strong growing consulting team.

Job Description

Archetype is seeking a Data Scientist to work with our customers and prospects to educate them on machine learning best practices and implantation.  This role’s responsibilities include:

  • Working with prospects’, customer’ and Archetype’s executives, data analyst, product managers, data architects, and engineers to define requirements, design solutions, and build/test/deploy these solutions

  • Be deep and broad with your technical and functional skill set to support end-to-end analytics across a variety of industries

  • Stay up to speed on emerging technologies and dynamic in how we evolve our approach for our customers

  • Proactively identifying opportunities for upsell and account expansion

  • Support sales processes by participating in scoping calls, solution design workshops, developing estimates and prototyping solutions

  • Most of the work can be managed remotely but must be able and willing to travel when needed

Required Qualifications: (Must Have)

  • 3-5 years building statistical and machine learning models with hands-on knowledge of applying Data Science concepts to business challenges including customer churn, customer segmentation, and product and services based neural networks

  • Demonstrated experience evaluating complex business and technical requirements and formulate clear, concise documentation

  • Expert knowledge of one or more data science tools including: Dataiku, DataRobot, Jupyter Notebooks, Pandas, SciPy, Scikit, PyTorch and/or TensorFlow

  • Experience/Familiarity using most of these ML techniques: Clustering, Regression (Multivariate, Logistic, etc), Support Vector Machines, Classification, Graphical Models, Bagging, Boosting, Decision Trees etc.

  • Analytical and problem-solving experience, exposure to large-scale data warehouses

  • Advanced experience in performing exploratory data analysis, feature engineering, data normalization and hyperparameter tuning

Preferred Qualifications: (Nice-To-Have)

  • Data driven mindset with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics. MS/PhD a plus

  • Experience with a statistical programming language like R or Python preferred

  • Prior work experience in a business analytics space would be highly valued

  • Exposure to multiple BI Tools: Tableau, ThoughtSpot, Looker, Sigma, PowerBI

  • Exposure to multiple Data Warehousing platforms: Snowflake, Azure, AWS, Oracle

  • Experience using statistical computer languages such as Python, R, Scala and Sql

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