As a BIE in the team, you will be driving the analytics roadmap and will provide descriptive and predictive solutions to the marketing and product management team through a combination of data mining techniques as well as use statistical and machine learning techniques. You will need to collaborate effectively with internal stakeholders, cross-functional teams to solve problems, create operational efficiencies, and deliver successfully against high organizational standards. Responsibilities Understand the business reality behind large sets of data and develop meaningful solutions comprising of analytics as well as marketing management You will need to have an AI first mindset in evolving and becoming more agile with business analytical requirements Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area Innovate by adapting new modeling techniques and procedures You should be passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets. You will extract huge volumes of data from various sources and message streams and construct complex analyses. You will implement data flow solutions that process data real time on message streams from source systems. You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training. You will mentor junior resources in building scalable systems, drive a lot of automation by converting existing resources into Quick dashboards Basic Requirements : 4+ years of professional experience 4+ years of SQL experience Experience programming to extract, transform and clean large (multi-TB) data sets Experience with theory and practice of design of experiments and statistical analysis of results Experience with AWS technologies Experience in scripting for automation (e.g. Python) and advanced SQL skills. Experience with theory and practice of information retrieval, data science, machine learning and data mining Preferred qualifications Experience working directly with business stakeholders to translate between data and business needs Experience managing, analyzing and communicating results to senior leadership Knowledge of data warehousing and data modeling Joining the Amazon team means partnering with a dynamic and creative group who set a high bar for innovation and success in a fast-paced and changing environment. The Business Analyst is responsible for being able to influence critical business decisions using data and providing insight to category teams to be able to act. The successful candidate needs to have : A passion for numbers, data and challenges. High attention to detail and proven ability to manage multiple, competing priorities simultaneously. Excellent verbal and written communications skills. An ability to work in a fast-paced, complex environment where continuous innovation is desired. Bias for action and ownership. A history of teamwork and willingness to roll up one’s sleeves to get the job done. Ability to work with diverse teams and people across levels in an organization Proven analytical and quantitative skills (includes the ability to effectively use tools such as Excel and SQL) and an ability to use hard data and metrics to back up assumptions and justify business decisions. Key job responsibilities Key job responsibilities 1. Influence business decisions with data. 2. Use data resources to accomplished assigned analytical tasks relating to critical business metrics. 3. Monitor key metrics and escalate anomalies as needed 4. Provide input on suggested business actions based on analytical findings.