Senior Analyst - Analytics

You will play a crucial role in enhancing the Analytics capabilities for our businesses. Your responsibilities will include engaging with key stakeholders to comprehend Fidelity's sales, marketing, client services, and propositions context. You will collaborate with internal teams such as the data support team and technology team to develop new tools, capabilities, and solutions. Additionally, you will work closely with IS Operations to expedite the development and sharing of customized data sets. Maximizing the adoption of Cloud-Based Data Management Services will be a significant part of your role. This involves setting up sandbox analytics environments using platforms like Snowflake, AWS, Adobe, and Salesforce. You will also support data visualization and data science applications to enhance business operations. In terms of stakeholder management, you will work with key stakeholders to understand business problems and translate them into suitable analytics solutions. You are expected to facilitate smooth execution, delivery, and implementation of these solutions through effective engagement with stakeholders. Your role will also involve collaborating with the team to share knowledge and best practices, including coaching on deep learning and machine learning methodologies. Taking independent ownership of projects and initiatives within the team is crucial, demonstrating leadership and accountability. Furthermore, you will be responsible for developing and evaluating tools, methodologies, or infrastructure to address long-term business challenges. This may involve enhancing modelling software, methodologies, data requirements, and optimization environments to elevate the team's capabilities. To excel in this role, you should possess 5 to 8 years of overall experience in Analytics, with at least 4 years of experience in SQL, Python, open-source Machine Learning Libraries, and Deep Learning. Experience working in an AWS Environment, preferably using Snowflake, is preferred. Proficiency in analytics applications such as Python, SAS, SQL, and interpreting statistical results is necessary. Knowledge of SPARK, Hadoop, and Big Data Platforms will be advantageous.,