• Data Analytics Associate

    Job Locations US-IL-Chicago
    # of Openings
    1
    Category
    Consulting
    Type
    Regular Full-Time
  • Overview

    Stax Inc., a global strategy consulting firm serving industry-leading corporate and private equity clients, is recruiting a Data Analytics Associate to join our team. Stax is a fast-paced firm, where actionable results and quality work are valued, and time spent on client sites is kept to a minimum. At all levels of the organization, our people are bright, driven, and able to excel. 

     

    During your time at Stax, you’ll consistently face intellectually challenging projects with clients that range from Fortune 500 companies to the largest LBO firms globally. Working across a wide spectrum of industries on short-term engagements designed to last 4-12 weeks, you’ll gain new hand-on experiences with each project you encounter.

     

    At Stax, you’ll also have incredible opportunities to build your consulting career. Our staff works side by side with—and learns from—some of the smartest people in the business. Our entrepreneurial approach to work and broad client base creates immediate opportunities for client exposure, providing enormous potential for career progression. Senior Associates work directly with all levels of the firm to diagnose our clients’ most pressing issues while identifying new opportunities for value creation and accelerating growth.

     

    Life at Stax is unique - our goal is to empower and challenge employees, while supporting a reasonable work/life balance. No question: you’ll work hard. However, unlike other firms where you might uproot your life for weeks or months at a time, our team spends far less time on the road. As such, creating time for professional and personal development, allowing great people and teams to grow as well as get involved in our communities.

     

    Our entire staff is intelligent, innovative and - most importantly - willing to roll up their sleeves. If you’re willing to dive in, work with talented team members and drive impact from day one, Stax is the perfect environment for you. 

     

     

    WHY STAX

    • High-profile engagements with Fortune 500s and half of the largest 20 LBO firms globally.
    • Solve real-world problems quickly, using data and insights to create actionable recommendations within 4−12 weeks.
    • Unparalleled immersive learning opportunities in a fast pace environment.
    • Direct client engagement with unrivaled exposure to different methodologies, perspectives and situations stemming from an array of project types across sectors.
    • Team-based, collaborative philosophy creates opportunities for all to contribute and have direct impacts on the client’s success as well as the firm’s.
    • Unmatched opportunities for personal growth and career development based on the merits of your work.
    • Smarter, more strategic approach to generating higher value outcomes in shorter time periods.
    • Good people who genuinely care about the firm’s success and are consistently exploring ways to improve and build upon its accomplishments.

    Responsibilities

    As a Data Analytics Associate, you will be part of our client engagements working closely with project teams to identify data needs, sources, and structure to support client issues, and to support private equity clients in better understanding and valuing potential investments. You will utilize rigorous business analytics, statistical models, and data science to identify actionable insights and ultimately develop strategic plans from this information to help our clients grow organically and make better investment decisions.

     

    You will help summarize and present key findings, and work closely with managers and directors to convert your team’s findings into valuable insights and actionable recommendations. You will support work streams, modules, and — after a period of time — own work streams. You will have exposure to a broad array of client needs and industries.

     

    Specific responsibilities will include:

    • Conduct in-depth business research and analysis in support of client business objectives.
    • Work closely with project leads to design and structure research and analysis plan for project work, gather data, perform analysis and interpret the outcomes.
    • Perform rigorous economic and business analysis including but not limited to market sizing, forecasting growth, customer segmentation, lifetime value, and supply/demand studies.
    • Perform data extraction, quantitative analysis, multivariate regression and predictive modeling on large data sets and data streams using various statistical programming (R, SPSS, Python).
    • Leverage machine learning techniques such as clustering, decision trees and association rule mining to extract knowledge from data.
    • Develop and test custom modeling, evaluate and select sampling methods and design experiments.

    Qualifications

    • Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Science, or a related quantitative discipline.
    • 1-3 years of data analytics experience preferably with a strategy consulting firm, strategic planning/corporate strategy group or private equity/venture capital firm.
    • Demonstrated experience in performing rigorous economic and business analysis including but not limited to market sizing, forecasting growth, customer segmentation, lifetime value and supply/demand studies.
    • Demonstrated experience and proficiency in large data manipulation in R or Python.
    • Excellent strategic thinking, understanding of business research and analysis.
    • Proven written, verbal and presentation skills that demonstrate the ability to frame ideas that capture appropriate details and structure output logically. 
    • Detail oriented and proven ability to multitask and work in a fast-paced, time-sensitive environment.
    • Demonstrated proficiency in advanced Microsoft Excel and PowerPoint functions.

    Options

    Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
    Share on your newsfeed