[ref. d3011101] Sales Ex - COE - Client Success Data Science Associate Manager
About Accenture:
At Accenture, we believe your career is about what you want to be and who you want to be. It’s about bringing your skills, your curiosity, and your best true self to your work. Here, you’ll match your ingenuity with the latest technology to do incredible things.Together, we can create positive, long-lasting change.
We are Sales Excellence:
Sales Excellence at Accenture empowers our people to compete, win and grow. We provide everything they need to grow their client portfolios, optimize their deals and enable their sales talent, all driven by sales intelligence.
The team will be aligned to the Client Success, which is a new function to support Accenture’s approach to putting client value and client experience at the heart of everything we do to foster client love. Our ambition is that every client loves working with Accenture and believes we’re the ideal partner to help them create and realize their vision for the future – beyond their expectations.
You are:
An experienced data scientist with a flair for turning data into business insights. You enjoy searching for patterns and connections in data to discover trends, root causes and solutions. While logical and objective in your approach, your true superpower is helping others to see how things can be done differently.You use AI modeling to test theories and identify ways to improve processes.
The work:
The Center of Excellence (COE) enables Sales Excellence to deliver best-in-class service offerings to Accenture leaders, practitioners, and sales teams.
As a member of the COE Analytics Modeling Analysis team, you will generate business insights to help Accenture to improve its processes, boost sales and maximize profitability.
You will build models and scorecards that help business leaders to understand trends and market drivers. You will work closely with operations teams to turn these insights into user-friendly solutions. Managing access to tools and monitoring their usage
You will:
- ETL raw data from the source systems across business areas and transform it into structured and usable formats for analysis and modeling purposes.
- Apply statistical, machine learning, and NLP techniques to analyze data, identify patterns, and extract meaningful insights.
- Develop machine learning or deep learning models to solve complex business problems or operations and implement and manage the models in the cloud platform.
- Interpret and present findings to technical as well as non-technical audiences in a clear and actionable manner.
- Identify Gen AI use cases leveraging various LLMs and design and conduct pilot projects to explore their feasibility and value.
- Develop Gen AI-based solutions or capabilities collaborating with cross-functional teams including data engineers and business stakeholders.
- Ensure data compliance with privacy regulations and implement data security measures.
- Stay updated with latest developments in data science and Gen AI.