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About the role
We are expanding our highly skilled team and actively seeking a proficient, talented, and ambitious Data Scientist to strengthen our demand planning team within o9. Your role will be pivotal in comprehending forecasting challenges faced by customers, particularly in Retail and CPG sectors, designing tailored solutions, creating and implementing models, validating results, and effectively communicating complex ideas to both clients and internal teams. What you ll do for us Use latest advancements in AI/ML to solve business problems Apply a variety of forecasting techniques (statistical time series models and machine learning models) to solve challenging time series forecasting problems Fine-tune models for demand sensing/forecasting, anomaly detection, history correction and outlier detection, pricing modeling, explainability of results (Explainable AI), etc. Analyze problems by synthesizing complex information, evaluating alternate methods, and articulating the result with the relevant assumptions/reasons Apply common business metrics (Forecast Accuracy, Bias, MAPE) and generate new ones as needed Conclude and present results highlighting key insights and findings to customers and internal teams Work collaboratively with Clients, Project Management, Solution Architects, Consultants, Data Engineers and Product Management to ensure successful delivery of o9 projects What you ll have... Overall 4+ years data science experience 2+ years of commercial data science experience in Demand Planning, Predictive Analysis, Demand Forecasting, Retail forecasting, or similar with time series use-cases Deep Knowledge of statistical and machine learning algorithms, identifying and collecting relevant input data, feature engineering, tuning, and testing Strong and independent mind to analyze and distill key insights from customer datasets to come up with the right methodology (level of forecasting, slicing datasets for localized and global models, parameter fine-tuning, feature engineering) Strong experience in quickly analyzing input data to assess quality and usability of input data to be fed to machine learning models Exposure to high paced experimentation including feature engineering, parameter tuning and optimization of machine learning models Education: Master s in Computer Science, Mathematics, Statistics, Economics, Econometrics, Engineering, or related field Tools: Python, Pyspark, Machine Learning libraries, SQL, building models in platforms like Power BI or Tableau 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. At o9, This is not limited by hierarchy, distance, or function. Preferred Experience Exposure to distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, or related Big Data technologies Experience in implementing planning applications will be a plus
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