Engineer III Specialist- Data Science

Job Description

What you will be doing As the AID Engr III Spec - Data Science - AI Product Manager for Business Enablement Organization, you will be responsible for Business engagement, architecting and building innovative solutions by applying cutting edge data science techniques. Engaging closely with the business stakeholders, understand problem statements and incubate ideas and models. Discovering insights using data modeling and analysis techniques that will guide strategic decisions and uncover optimization opportunities. Creating data science driven solutions that drive product effectiveness, personalization, better customer experience and operational efficiencies. Working closely with the stakeholder to prioritize the use cases and build the roadmap. Working with a talented team of data analysts, software developers and data science professionals who will play a key role in developing and delivering the next generation AI/ML solutions to the business. Having a passion to understand domains, systems and be able to associate business opportunities to this understanding and create analytical solutions Strategies and opportunities where data science and AI can be leveraged. Cross-team collaboration Working closely with other AI D pillars like AI Center, Data engineering and ML engineering and other groups Performing thorough data analysis, uncover opportunities and address business problems. Assertive and objective decision-making skills with the drive to deliver and arrive at solutions. Diagnosing business bottlenecks and provide prescriptive recommendations for stakeholders. What we are looking for You have excellent analytical skills, and are eager to work in a collaborative environment with global teams to drive data science applications for business problems, develop end-to-end analytical solutions and communicate insights and findings to leadership. You have strong expertise in VCG digital sales, Retail and in driving use cases that drive personalization. You are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various stakeholders and cross functional teams to implement data science driven business solutions. You will need to have: Bachelors degree or Four or more years of work experience. Three or more years of experience practicing data science in business. Prior experience working in a Product team and having a product mindset. Extensive experience with AI solutioning in the Networks related areas like workforce optimization, reliability, Energy optimization etc. Strong communication, presentation and collaboration skills. Good Consumer knowledge and experience. Excellent analytical skills and use case prioritizations to build the roadmap at the product level in alignment with the business and stakeholders. Excellent knowledge on machine learning and predictive modeling. Experience in identifying business opportunities and build impactful data science driven use cases. Excellent problem solving and critical thinking capabilities. Experience using different statistical/modeling techniques. Excellent working knowledge of SQL for data analysis and EDA using Python. Ability to create compelling narratives and articulate insights through strong storytelling skills. Experience working in analytics projects. Even better if you have one or more of the following: Experience interacting and collaborating deeply with other lines of business the ability to work across cross cultural teams. Experienced with A/B and Multivariate testing, and should be able to provide recommendations accordingly. Expertise in performing thorough data analysis using database queries, spreadsheets, statistical packages tools, and communicate results effectively. Experience with dev-ops and agile models, as well as more traditional functional operating models. Ability to interact and provide executive level communications to senior management. Exposure to GenAI and Prompt engineering. Experience managing time-bound project deliverables for multiple stakeholders.