Data Scientist

Data is now more important than ever, and the information distilled from it is crucial for making meaningful decisions. Our team 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 a 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.

Responsibilities:

• 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.
• 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+ years.
• Prior experience with building ML models.
• Prior experience with SQL.
• Knowledge of statistical techniques.
• Experience working with spatial data will be an added advantage.