Data Scientist/Engineer

Ikoyi, Lagos, Nigeria

About Us:

We are an innovative technology company building AI-powered applications that transform industries. Our mission is to integrate cutting-edge artificial intelligence into real-world products that deliver measurable business value.


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:

  1.           Design, build, and maintain data pipelines for AI/ML training and inference.
  2.           Clean, normalize, and structure large datasets from multiple sources.
  3.           Create datasets for supervised/unsupervised learning tasks.
  4.           Perform exploratory data analysis (EDA) to identify patterns and insights.
  5.          Collaborate with AI engineers to create features that improve model performance.
  6.           Build dashboards and reporting tools to monitor AI system outputs.
  7.           Ensure data quality, security, and compliance with regulations.


  1. 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.

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