Yeah, us too!
600+ enterprise customers in 60 countries
50% of Fortune 100 companies are customers
24 of the Gartner Top 25 Supply Chain are customers
So, yes, were all about business. But were also all about sustainability, see our 2017 Green Award **
ICYMI: We were named to the 2017 Best and Brightest Company in the US of A and in Metro Detroits 2017 Best and Brightest Company list
Were well funded, fun and focused on building the very best in supply chain and we want YOU to help us build complex models that allow global companies to quickly, safely model supply chain impacts.
Dont believe us - read the Gartner Supply Chain Masters and youll learn that nearly all of the Gartner Supply Chain Top 25 use our solutions to tackle the most complex supply chains issues the world has ever seen.
Smart, energetic and ready to make your mark in a best in class enterprise software company? Join our herd!
** from Supply and Demand Chain Executive
- Research, design and prototype novel models based on machine learning, data mining, and statistical modeling to solve hard analytics problems, where the problems may range from exploratory to highly applied
- Keep abreast of the latest developments in the field by continuous learning and pro-actively champion promising new methods relevant to the problems at hand
- Work with team to make algorithms production quality and scalable
- Work with Product Management to deliver effective software solutions to our clients business problems
- Experience with designing and implementing machine learning and data mining algorithms in production systems along with the related automated data pipelines
- Excellent working knowledge and real-life experience implementing machine learning techniques and algorithms including the following:
- Supervised and unsupervised Machine Learning areas, such Regression, Classification, Clustering and Recommender Systems.
- Linear and non-linear models - Linear, Lasso, Ridge Regression, Logistic, Multinomial, Ordinal Regression etc.
- Advanced Machine Learning algorithms - SVM, Random Forest, Gradient Boosting, Neural Networks.
- Clustering Algorithms - k-means, Hierarchical Clustering etc.
- Ensemble methods like bagging, boosting and stacking.
- Feature Engineering
- Feature Selection techniques Correlation based, model based
- Understanding of Bias/variance trade-off. Underfitting/Overfitting
- Dimensionality reduction techniques such as PCA, SVD etc.
- Comprehensive knowledge of statistics including the following:
- Resampling techniques Bootstrapping, Cross-validation, Under/oversampling
- Classic Time Series Algorithms Exponential Smoothing, ARIMA. Ability to detrend and de-seasonalize time series.
- Residual Analysis
- Hypothesis testing
- Monte-Carlo simulation
- Bayesian Statistics
- Accuracy Metrics AIC, BIC, AICc, RMSE, MAPE, WMAPE, MAE, ME
- Experience in data wrangling including
- Data transformation techniques Normalization, Scaling and Centering, Box-Cox transformation.
- Anomaly Detection
- Outlier Adjustments
- Imputation techniques
- Data aggregation and disaggregation techniques
- Experience with demand forecasting for commercial products and related problems like:
- Hierarchical Forecasting
- Demand Sensing
- Temporal Aggregation
- Diffusion Models
- Promotion Modeling
- Intermittent Demand Forecasting
- MS or PhD in statistics, mathematics, theoretical science, operational research, computer science or related relevant domains
- Practical knowledge of one or more NoSQL databases
- R and Python
- Experience in data visualization
- Strong communication skills
- At least three years of professional experience outside academia
- Strong publication record in top conferences and journals