Data Scientist

Data is now more important than ever, and the information distilled from it is crucial for making meaningful decisions. GeoIQ is a product developed by data scientists for data scientists. We obtain, visualise, and analyse data from heterogeneous sources to build smarter variables that aid decision-making.

As part of the data science team, you will be responsible for building predictive models and day-to-day analysis for our clients, building algorithms on the data collected from hundreds of sources to build location-defining attributes.

As a Data Scientist at GeoIQ, you will play a crucial role in extracting valuable insights from vast and complex datasets to support our hyperlocal location AI platform and enable businesses to make precise and data-driven decisions.

Responsibilities:

• Collaborate with cross-functional teams to understand business requirements and define data science project objectives.
• Collect, clean, and preprocess large-scale datasets from diverse sources to ensure data quality and suitability for analysis.
• Develop and implement machine learning algorithms and predictive models to solve business problems and optimise decision-making processes.
• Conduct in-depth data analysis, exploratory data analysis, and statistical hypothesis testing to identify patterns, trends, and insights.
• Use advanced statistical techniques and mathematical modelling to uncover relationships between variables and predict outcomes.
• Create and maintain data pipelines and automation processes for efficient data ingestion, transformation, and storage.
• Build and deploy data-driven dashboards, visualisations, and interactive reports to communicate findings to stakeholders effectively.
• Continuously monitor model performance, conduct A/B testing, and fine-tune models to improve accuracy and efficiency.
• Collaborate with software engineers to integrate machine learning models into production systems.

Requirements:

• Proficient in Python.
• Work experience: 2-8 years.
• Prior experience with building ML models.
• Prior experience with SQL.
• Knowledge of statistical techniques.
• Experience with working on Spatial Data will be an added advantage.