Noemdek's advisory practice was established to support international strategic advisory firms with relevant local expertise. We are able to deliver on our promise to our partners because we have a strong team of people trained at some of the world's top universities who have immersed themselves in the Nigerian business community. In addition to partnering with international advisory firms, Noemdek also works directly with clients in the healthcare, financial services, consumer goods and oil and gas industries. Similar to our venture capital business, we are fully committed to helping our clients with solutions that will ensure they have a lasting competitive advantage. Therefore, we look beyond standard solutions to develop effective partnership structures, new insights, mobilize organizations, drive tangible results, and make public and private institutions more capable. Our customized approach combines deep insight into the dynamics of companies and markets with close collaboration at all levels of the client organization. This ensures that our clients build more capable organizations, and secure lasting results. We seek to be agents of change-for our clients, our people, and society overall. Noemdek also leverages its relationships with investors to support clients in raising capital to fund acquisitions.
We are seeking a Data Systems & AI Insights Engineer to own our data infrastructure and analytics pipelines that power AI models. This hybrid role combines data engineering (ensuring clean, structured, and accessible datasets) with data science (model evaluation, feature engineering, performance analytics). You will work closely with the AI engineering team to provide the high-quality data needed for effective AI solutions.
Key Responsibilities:
- Design, build, and maintain data pipelines for AI/ML training and inference.
- Clean, normalize, and structure large datasets from multiple sources.
- Create datasets for supervised/unsupervised learning tasks.
- Perform exploratory data analysis (EDA) to identify patterns and insights.
- Collaborate with AI engineers to create features that improve model performance.
- Build dashboards and reporting tools to monitor AI system outputs.
- Ensure data quality, security, and compliance with regulations.
Requirements:
- Strong SQL and Python skills for data manipulation and automation.
- Experience with data engineering tools (Airflow, dbt, Kafka, Spark, etc.).
- Hands-on experience with cloud data platforms (AWS Redshift, BigQuery, Snowflake, etc.).
- Familiarity with data science workflows (pandas, NumPy, scikit-learn, visualization libraries).
- Knowledge of data quality and validation best practices.
- Experience building ETL/ELT pipelines.
Method of Application
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