About the role 

With the latest increase in the valuation from $1B to $2.7B, our client is one of the fastest-growing technology companies in the world today. Their mission is to digitally transform planning and decision-making for the enterprise and the planet. 

Their platform, is the premier AI-powered, cloud-native platform driving the digital transformations of major global enterprises including Google, Nike, Walmart, ABInBev, Starbucks, and many others.

The role is aimed to operationalise various kinds of descriptive, predictive and prescriptive analytics and data science relevant in the planning space. Understand business; identify areas of improvement opportunities; collect and analyse data; build models in R/Python; and present results & insights using the client's platform.

Responsibilities

• Apply a variety of machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimisations etc.) to their real-world advantages/drawbacks
• Develop and deploy models for demand sensing/forecasting, optimisation (Heuristic, LP, GA etc), Anomaly detection, Simulation and stochastic models, Market Intelligence etc.
• Use latest advancements in AI/ML to solve business problems
• Analyse problems by synthesising complex information, evaluating alternate methods, and articulating the result with the relevant assumptions/reasons
• Application of common business metrics and the ability to generate new ones as needed
• Work collaboratively with Clients, Project Management, Solution Architects, Consultants and Data Engineers to ensure successful delivery of projects

Requirements

• Experience: 8+ years of experience in the field of Data Science and Analytics
• Experience in time series forecasting in scale using heuristic based hierarchical best-fit models using algorithms like exponential smoothing, ARIMA, prophet and custom parameter tuning
• Experience in building scalable ML frameworks for demand sensing including Identifying and collecting relevant input data, feature engineering, tuning, and testing.
• Experience in applied analytical methods in the field of Supply chain and planning, like demand planning, supply planning, market intelligence, optimal assortments/pricing/inventory etc.
• Experience with SQL, databases and ETL tools or similar is optional but preferred
• Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies
• Experience with Deep Learning frameworks such as Keras, Tensorflow or PyTorch is preferable but not essential
• Experience in implementing planning applications will be a plus

• Education: Bachelors Degree in Computer Science, Mathematics, Statistics, Economics, Engineering or related field or Masters Degree in Computer Science, Applied Mathematics, Statistics, Engineering, Business Analytics, Operations, or related field

• Skills: Strong programming skills and experience in using Python and/or R for Data Science
• Strong analytical techniques, data mining knowledge and proficiency in handling and processing large amounts of data is needed
• Deep Knowledge of statistical and machine learning algorithm
• Understanding of Supply Chain Concepts will be preferable

• Characteristics: Strong presentation and communications skills. You thrive in a fast paced, challenging environment, where this is much white space and problem solving is at the heart of what drives your analysis.

• We really value team spirit: Transparency and frequent communication is key, regardless of hierarchy, distance, or function

What's in for your

• Competitive salary
• Tech tools: Complementary Mac or PC laptop.
• Enjoy yourself: Unlimited paid time off.
• Get social: When we work from home, we play from home with fun after-work activities like Friday Socials. If you’re in the office, feel free to join these events in person.
• Flat organisation: With a very strong entrepreneurial culture (and no corporate politics).
• Support network: Work with a team you can learn from and every day.
• Diversity: We pride ourselves on our international working environment.