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Lead Data Scientist

Lead Data Scientist

Job Locations 
US-IL-Chicago
Category 
Product / Engineering
Type 
..

More information about this job

Overview

Shiftgig, one of Chicago’s hottest and fastest growing technology companies, is actively seeking a Lead Data Scientist in our Chicago office. We are a tech company in a non-tech space and as such, we have a lot of interesting problems to solve. Our architecture is centered around internal and external APIs with consuming clients being our single page applications and native mobile apps.

Responsibilities

What You'll Do:

  • Manage the data science team including goal setting, kpis, and future hiring; create an environment in which your team members are continuously challenged and exposed to new opportunities
  • Maintain a  roadmap for data science initiatives that aligns with the company’s strategic objectives and product / engineering projects  
  • Manage data science sprint planning and user stories
  • Working with data engineering, strategize and build key data sets and user behavior models to empower exploratory analysis and influence product / business decisions
  • Work with PMs / engineers to deliver products and features based on DS algorithms and learning      
  • Find the right resource allocation balance between exploratory activities and product / feature creation
  • If you aren’t already, become an expert on marketplace matching, reputation / feedback, and demand planning related to optimizing LTV / CAC / etc. in a two-sided marketplace; help define A/B testing and RCT experiments to improve our marketplace dynamics
  • Work collaboratively with business analysts in finance and sales to ensure processes and tools are in place so the company’s business intelligence needs are met

 

Tools we use:

  • Python
    • Basics: Numpy, scipy, sklearn, pandas
    • Modelling: Theano, Tensorflow, Keras
    • Parallelization: Celery, Multiprocessing
    • Additional: NLTK, matplotlib, seaborn
  • Databases:
    • PostgreSQL
    • MongoDB
    • Cassandra
  • Github
  • Supplemental Skills that would round out Data Science:
    • Docker, Vagrant, and AWS
    • Flask
    • Hadoop and Spark

Qualifications

What Were Looking For:

  • 5+ years of experience working with very large datasets of varied levels of structure
  • BA/BS/PhD in quantitative field
  • Extensive experience performing exploratory analysis guided by scientific principles, feature engineering, model training, testing and validation of the data models to create precise, high performing and reliable models to be used in product
  • Experience with data engineering including designing and implementing distributed data systems, data ingestion processes, ETL / ELT frameworks
  • Experience prioritizing product ideas by forecasting business impact/ROI
  • Demonstrated ability to use data to drive business impact
  • Management experience
  • Nice to have
    • Experience with a multi-sided marketplace
    • Experience in the employment / labor / gig economy space
    • Solid understanding of supply / demand economics
    • Experience with pricing
  • Desire to be a part of Shiftgig’s vision of  creating financial opportunity for the hourly workforce and our mission to connect millions of people with millions of shifts
  • Unquenchable curiosity and love of learning

 

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

 

 

SG123

About Shiftgig

Shiftgig was founded on the simple premise that many people want flexible work opportunities that fit into the rest of their lives, so we build technology that is focused on one thing: connecting people who want temporary work right now with businesses who need them.

 

We’re fulfilling our mission of connecting millions of people with millions of shifts via our mobile apps and platform. Our apps make it easy for businesses to post gigs and for qualified and skilled workers to claim them. Our platform handles shift fulfillment, and handles all the messy bits associated with labor management.

 

We are a tech company in a non-tech space with many interesting problems to solve. Our architecture is centered around internal and external APIs where the consuming clients are our single page applications and native mobile apps.