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Chief Data Scientist
2 weeks ago
As a Senior Data Science Consultant, you will be responsible for guiding optimal decisions across various key pricing initiatives related to acquisition volume, quality, revenue growth and pricing elasticity by leveraging knowledge of experimental design and testing frameworks like A/B testing, Multi-armed Bandit testing etc.
You will research and build proof-of-concept models utilizing various machine learning techniques & traditional statistical techniques to drive optimal business decisions for device roadmap assortment, arbitrage analysis, and pricing elasticity.
Additionally, you will build financial models leveraging acquisition modeling and other machine learning techniques while partnering with base management on optimal assortment and leveraging their acquisition quality index for predictive modeling.
You will create various device assortment forecasting models while partnering with brand and FP&A during OEM negotiations to assist with scenario planning during the modular roadmap process.
Furthermore, you will research and evaluate price moves to competition and gray market pricing to determine arbitrage impact and provide analytics on optimal thresholds of arbitrage potential to mitigate subsidy loss.
You will also partner with Reporting & Analytics on one data initiative to bring in retailer POS data to aid in analytics across retailers and channels.
Moreover, you will work with diverse teams and stakeholders, keep project leads updated on progress, and ensure projects move forward promptly.
Key responsibilities include identifying high value opportunities for applying Advanced Analytics, Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT), developing and deploying innovative tailored solutions in manufacturing environment.
Conduct in-depth data analysis to identify trends, patterns, user behaviors and corresponding business impact to inform product development decisions.
Utilize data science techniques and statistical methods to conduct exploratory analyses and develop predictive models that drive business insights and decision-making.
Develop and maintain a balanced set of KPIs and performance metrics that assess the success of product initiatives, including product adoption, revenue impact, user and customer retention.
Utilize various data analysis tools and methodologies to extract actionable insights from large datasets, covering both product usage and financial data.
Lastly, create and present data-driven reports and presentations to stakeholders, demonstrating how product improvements positively impact the bottom line.
Requirements- Proficiency in Python for Data Science and SQL
- Advanced knowledge of Classification, Regression, and Forecasting models
- Strong skills in Model Packaging & Deployment and Model Packaging & Deployment
- Capability in Data Science on AWS, GCP, or Azure
- Experience with Technical Leadership and Task Delivery in a data science context
