Associate Director, Data Science at Method

| Charlotte, NC | Remote
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Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams [based in New York, Charlotte, Atlanta, London, and remote] work with a wide range of organizations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Your role is to help build data analytics and predictive models that support various loyalty campaigns for an online grocery store. This includes building end-to-end machine learning solutions in retail and e-commerce, while working closely with the Marketing and Finance teams. You will help monitor, test & provide prescriptive insights for various elements of loyalty efforts including loyalty campaigns, personalized offers for the loyalty program, pricing optimization, ML powered campaigns for the Client’s marketing and demand forecasting for supply chain.


  • Apply knowledge of data science techniques and statistics into production, with a robust commercial approach, being mindful that Marketing operationalization is a key success criteria.
  • Implement a highly visual and commercial approach when delivering data science projects that engages and challenges the thinking of non-technical audiences.


  • 3-5 years working in the data science field and applying it to real world commercial problems with clearly defined and measured business benefits.
  • Work as a self-starter and hands-on technical specialist, take the ownership of projects.
  • Strong statistical background applied across a number of areas including classification, predictive modeling, recommendation systems.
  • Experience using supervised learning techniques including classification, regression, prediction, forecasting, multivariate analysis, seasonality adjustment. 
  • Experience using statistical techniques such as Regression (Linear, Kernel), Classification (Logistic Regression, Bayesian inference, Support Vector Machines, Decision Trees, Random Forest), Clustering (Nearest Neighbor), dimensionality reduction, principal component analysis, causal inference, Ensemble models. 
  • Desired experience using unsupervised and reinforcement learning, NLP, clustering, anomaly detection, ANN, GAN, Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) / LSTM. 
  • Comprehensive proficiency in key programming and scripting languages (e.g. Python, R, SNOWFLAKE, SQL, et)
  • Knowledge of Micro-strategy (desirable)
  • Clear communication skills to translate data science into meaningful insight for the Marketing team.

Why Method?

We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels.

We believe in work/life balance. Seriously. We offer a ton of competitive perks, including:

  • Continuing education opportunities 
  • Flexible PTO and work-from-home policies 
  • 401K matching
  • Health, Dental and Vision benefits, starting on day 1
  • Friday company lunches, company outings, along with beer and a lot of snacks 
  • Health and wellness programs 
  • Other location specific perks (just ask!)

Next Steps

If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a blog, Twitter, GitHub, Dribbble or other platform.

* For information on how we process your personal data please see Privacy.

* If you are a California resident, more details on how we process your personal information can be found in the CCPA Recruitment Privacy Notice ("

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