Cisco is looking to drive its transformation into a data-driven digital organization by developing scalable data products, predictive models, and automated insights pipelines to address the evolving expectations of today's connected customers, partners, and Cisco sellers.
Requirements
- Proficient in Python and its data science libraries (pandas, NumPy, scikit-learn), as well as R, with strong skills in statistical analysis, machine learning fundamentals, and data visualization.
- Skilled in SQL for data transformation, modeling, and large-scale querying, with technical knowledge of data models, database design, data mining, and segmentation techniques.
- Experienced in building dashboards and analytics solutions in Power BI (or similar BI tools), transforming complex data into clear, actionable insights.
- Hands-on experience with data manipulation and ETL tools, including SQL and big-data technologies like Hadoop, along with familiarity with reporting and statistical packages such as Excel, SPSS, SAS, and Business Objects.
- Able to work with distributed computing tools
- Knowledge of data privacy, security, and governance processes
- Experience with machine learning and data-mining techniques
Responsibilities
- Build, test, and deploy predictive models and machine learning pipelines to support customer lifecycle analytics and digital engagement at scale.
- Transform complex, large-scale datasets through Python, SQL, and distributed computing tools to develop high-quality datasets and features for analytics and ML.
- Develop automated dashboards, visualizations, and analytics apps using Power BI to deliver real-time insights to partners and leadership.
- Identify, analyze, and interpret trends and patterns using advanced statistical, machine learning, and data-mining techniques; communicate insights with clarity.
- Collaborate closely with business and engineering teams to translate persona-specific use cases into scalable solutions, consolidating requirements and delivering cross-functional data products.
- Partner with data engineers and architects to design data pipelines, integrate new data sources, and validate data quality, completeness, and performance.
- Implement and maintain data privacy, security, and governance processes within analytics and ML workflows.
Other
- Currently enrolled in a certification program (e.g., Boot Camp, Apprenticeship, Community College with 0 years of relevant experience) or currently enrolled in an undergraduate degree program.
- Able to legally live and work in the country for which you are applying, without visa support or sponsorship.
- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Optional 10 paid days per full calendar year to volunteer
