*description*:
*key responsibilities*
- *data modeling and pipeline management*
- build and fine-tune classification models in the areas of spend management, contract management, and operational effectiveness.
- develop and maintain data pipelines and architectures for efficient data processing and analysis.
- stay informed of new techniques for predictive/prescriptive modeling.
- *automation development*
- identify and action upon opportunities to automate repetitive tasks from within the team.
- monitor and maintain automated processes to ensure optimal performance.
- mentor junior team members on automation skillsets.
- *insights & reporting*
- perform exploratory data analyses, which may include machine learning, to uncover trends, patterns, and insights from large and complex datasets.
- develop, test, and implement data-driven solutions to support business objectives.
- oversee the quality and effectiveness of team dashboards and reports.
- *data management & quality*
- design and implement data collection and data quality processes.
- ensure data integrity and consistency across multiple sources and systems.
- develop and maintain documentation for data processes and analysis specifications.
- *collaboration & communication*
- work closely with data engineers and business analysts to integrate data insights into production systems.
- communicate findings and insights to non-technical stakeholders through reports and presentations.
*qualifications*:
- * education*: master's degree in data science, analytics, statistics, computer science, mathematics, engineering, or a related field.
- *experience*: 4+ years of professional experience in data analytics, with a proven track record of building and tuning classification models.
- *language*: proficiency in english is required.
*technical skills*
- strong proficiency in python or r programming.
- experience utilizing statistical methods and machine learning techniques.
- expertise in building and deploying predictive models.
- proficiency in microsoft azure, including azure data factory and databricks, or a demonstrated ability to learn new tools and platforms
- understanding of data visualization tools, with a preference for power bi.
- experience with sql for data manipulation and querying.
- *data management*
- experience with data manipulation and cleaning tools (e.g., tidyverse, pandas, numpy).
- familiarity with data warehousing solutions (e.g., sql server, amazon redshift, google bigquery).
*soft skills*
- strong problem-solving skills and attention to detail.
- excellent communication skills, with the ability to convey technical concepts to a non-technical audience.
- ability to work independently and as part of a team in a fast-paced environment.
*preferred qualifications*
- certification in data analysis or related fields.
- experience with cloud platforms (e.g., aws, azure, google cloud).
- knowledge of agile methodologies and version control systems (e.g., git).
- *procurement background*: experience in procurement is an added advantage.