Data Science Senior Manager

Data Science Senior Manager

Description -

HP invites applications for a motivated and talented Data Science Senior Manager to join our AI for Inventory & Product placement team, nested within the GTM Advanced Analytics organization.

In this important role, you will employ implement advanced statistical and/or machine learning methodologies to maximize the forecasting accuracy in our models supporting global sales and inventory forecasts for thousands of products, distributors and resellers weekly. You will be involved in the design, development, training and validation of state of the art data science models (DeepAr, Transformers, Tree Based). You will be the central connection among Data Scientists, Data Engineers, MlOps and Stakeholders, ensuring that business needs are aligned with team efforts and focused on objectives.

Responsibilities:

• Advanced Machine Learning Design
  • Use R or Python to analyse and clean extensive datasets, ensuring actionable insights are extracted to optimize our algorithms.
  • Analyse and integrate various factors impacting inventory and supply chain decisions into data science models. (pricing, promotions, inflation, etc..)
  • Identify the best suited forecasting signals, as well as algorithms/models suited to the problem
     
• Machine Learning Forecasting
  • Ensure there is no leakage, and address signals drift in the forecasting pipelines 
  • Design, develop and validate the selected forecasting, backtesting and inference pipeline
     
• Engineering and forecasting inference
  • Work with MlOps and engineers to ensure the scalability and efficiency of the forecasting pipeline
  • Monitor accuracy at scale across thousands of products and distributors
  • Run anomaly detection techniques to identify edge cases and areas of improvement
  • Run A/B testing to replace and deploy new ML models with higher accuracy and more robust to pattern changes
    
     

Basic Qualifications:

• Working experience in Data Analytics or Data Science.
• Proven track record of success leading data science and/or data analytics teams.
• PhD degree in Business Analytics, Statistics or related field is a must.
• Experience with Pyspark is a must.
• Experience with Pytorch or Keras is a must.
• Experience in Supply Chain, Inventory Management or Distribution networks is a strong plus.
• Experience with Git and cloud-based notebooks are a plus.
• Proficiency in SQL, PowerBI is a plus.
• Technical Proficiency:
  • Strong proficiency with the design, development, and validation of advanced machine learning or statistical forecasting techniques in Python.
  • Strong knowledge regarding various industry standard and state of the art algorithms and models used in forecasting (DeepAr, Transformers, Neural Networks, Tree based algorithms, etc..)
     
• Communication Skills: Capability to extract requirements from users and adeptly communicate intricate data insights to data analysts, data scientists and data engineers.
  
  
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  Sales and Services Entity

Job -

Data & Information Technology

Schedule -

Full time

Shift -

No shift premium (Spain)

Travel -

Relocation -

Equal Opportunity Employer (EEO) - 

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

If you’d like more information about HP’s EEO Policy or your EEO rights as an applicant under the law, please click here: Equal Employment Opportunity is the Law Equal Employment Opportunity is the Law – Supplement