Senior Engineer Consultant - Data Science

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 :

(ref : hirist.tech)