Data Analyst

Sand Technologies is a fast-growing enterprise AI company that solves real-world problems for large blue-chip companies and governments worldwide.
We’re pioneers of meaningful AI : our solutions go far beyond chatbots. We are using data and AI to solve the world’s biggest issues in telecommunications, sustainable water management, energy, healthcare, climate change, smart cities, and other areas that have a real impact on the world. For example, our AI systems help to manage the water supply for the entire city of London. We created the AI algorithms that enabled the 7th largest telecommunications company in the world to plan its network in 300 cities in record time. And we built a digital healthcare system that enables 30m people in a country to get world-class healthcare despite a shortage of doctors.
We’ve grown our revenues by over 500% in the last 12 months while winning prestigious scientific and industry awards for our cutting-edge technology. We’re underpinned by over 300 engineers and scientists working across Africa, Europe, the UK and the US.
ABOUT THE ROLE
This role will be client-facing in our insurance domain and involve creating, analyzing and interpreting complex client data sets to provide valuable insights and support data-driven decision-making within the client organization.
Work closely with cross-functional teams, including business stakeholders and IT professionals. Expertise in data manipulation, statistical analysis, data visualization, and problem-solving will be crucial in uncovering patterns, trends, and opportunities that drive business growth.
RESPONSIBILITIES
Data Collection and Cleaning: Gather, extract, and organize data from various sources, ensuring its accuracy and completeness. Clean and preprocess data to prepare it for analysis.
Data Analysis: Perform exploratory data analysis, apply statistical techniques, and use data mining methods to identify patterns, trends, and insights from complex data sets.
Data Visualization: Create clear and compelling data visualizations, such as charts, graphs, and dashboards, to effectively communicate insights to stakeholders and facilitate understanding.
Data Modeling and Forecasting: Develop and implement statistical models and forecasting techniques to predict future trends and support business planning and decision-making.
Report Generation: Prepare and deliver reports and presentations summarizing analytical findings and recommendations to stakeholders at various levels of the organization.
Data Quality and Validation: Ensure the accuracy, consistency, and integrity of data through data validation, quality checks, and error identification and resolution.
Collaboration: Collaborate with cross-functional teams, including business stakeholders and IT professionals, to understand business requirements and provide data-driven insights.
Continuous Improvement: Stay updated with the latest tools, techniques, and best practices in data analysis and data visualization. Continuously enhance skills and knowledge to improve analytical capabilities.
Privacy and Compliance: Adhere to data privacy regulations and compliance requirements while handling sensitive and confidential data.
QUALIFICATIONS
Bachelor's degree in a quantitative field, such as Mathematics, Statistics, Economics, or Computer Science. A master's degree is a plus.
At least 5 years of professional experience as a Data Analyst or in a similar role, demonstrating proficiency in data analysis and statistical techniques.
Proficiency in data manipulation and analysis tools such as SQL, Python, or similar technologies.
Strong analytical and problem-solving skills with the ability to derive meaningful insights from complex data sets.
Experience with data visualization tools such as Tableau, Power BI, or similar software to create interactive and informative visualizations.
Familiarity with statistical analysis techniques and modelling approaches.
Knowledge of data querying languages (e.g., SQL) and databases.
Strong attention to detail and ability to work with large volumes of data.
Excellent communication and presentation skills to convey complex findings clearly and concisely.
Ability to work both independently and collaboratively in a cross-functional team environment.
Knowledge of insurance and familiarity with insurance-specific metrics and KPIs is a plus.

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