DATA SCIENTIST / ENGINEER AT NOEMDEK LIMITED | ENGINEERING JOBS IN LAGOS

About Company:

NoemDek Limited is an EPC Company incorporated in Nigeria in 2012, to provide specialized services to the Oil & Gas, Power Generation, FMCGs, etc. Over the past five years, the firm and its international partners have supported clients on large infrastructure projects and after-sales services to ensure the assets are maintained effectively and a client’s operations run smoothly

Job Description:

We are looking for a hybrid Data Systems & AI Insights Engineer to act as the bridge between our data infrastructure and our AI capabilities. In this role, you will be responsible for building the robust pipelines that feed our AI models while providing the analytical insights necessary to evaluate and improve their performance. You will ensure our machine learning projects are powered by high-quality, structured, and accessible data.

Requirements:

• Data Pipeline Development: Design and maintain scalable data pipelines optimized for both AI model training and real-time inference.

• Data Preparation: Clean, normalize, and structure large-scale datasets from disparate sources to ensure they are model-ready.

• Feature Engineering: Partner closely with AI engineers to engineer, test, and select features that directly enhance model predictive performance.

• System Monitoring: Build interactive dashboards and reporting tools to track AI output quality, system health, and drift.

• Data Governance: Implement and enforce strict data quality, security, and compliance protocols across all data systems.

• Exploratory Analysis: Conduct deep-dive analysis to identify data patterns, insights, and opportunities for model refinement.

Qualifications and Skills:

• Core Technical Skills: Advanced proficiency in SQL and Python for data manipulation, automation, and statistical analysis.

• Engineering Tools: Proven experience with modern data engineering frameworks (e.g., Airflow, dbt, Kafka, Spark).

• Cloud Infrastructure: Hands-on expertise with cloud-based data platforms (e.g., AWS Redshift, Google BigQuery, Snowflake).

• Data Science Workflow: Familiarity with standard libraries such as Pandas, NumPy, and scikit-learn.

• ETL/ELT Proficiency: Deep understanding of designing and optimizing end-to-end data pipelines.

• Quality Focus: Strong commitment to data validation best practices and troubleshooting.

Nice to Have

• Prior experience working with complex AI/ML datasets (specifically Computer Vision or NLP).

• Knowledge of ML model evaluation metrics and experimentation frameworks.

Salary

Application Closing Date: Not specified

Application Instructions:

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