Data Scientist

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.

We are recruiting to fill the position below:

Job Position: Data Scientist / Engineer

Job Location: Ikoyi, Lagos
Job Schedule: Full time

Role Overview

• 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.

Nice to Have:

• Experience working with AI/ML datasets (computer vision, NLP, tabular).
• Familiarity with ML model evaluation metrics and experimentation.