Senior Engineer Consultant - Data Science (4-14 yrs)

Job Description :

- Knowledge of experimental design and testing frameworks like A/B testing, Multi-armed Bandit testing etc. to guide optimal decisions across various key pricing initiatives related to acquisition volume, quality, revenue growth and pricing elasticity.

- Researching and building 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

- Building 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

- Creating 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

- Researching and evaluating 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

- Partnering with Reporting & Analytics on one data initiative to bring in retailer POS data to aid in analytics across retailers and channels

- Work with diverse teams and stakeholders, keep project leads updated on progress, and ensure projects move forward promptly.

- Identify high value opportunities for applying Advanced Analytics, Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT), and develop and deploy 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.

- Create and present data-driven reports and presentations to stakeholders, demonstrating how product improvements positively impact the bottom line

- Stay current with best practices in data analysis and data science to make well-informed data-driven recommendations.

Skills Required :

- 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