Data Analytics

Key Responsbilities & Accountabilities:

As a Data Analytics & BI Engineer, you will be a crucial player in our data-driven decision-making process. Your role will involve developing, optimizing, and maintaining our business analytics solutions, enabling stakeholders to access and utilize data for informed decision-making. through designing and delivering machine learning and advanced analytics solutions that solve real business problems. You will work closely with business teams, data engineers, and data visualization experts to build scalable models and translate data into actionable insights.

• Business Problem Solving:
  Partner with business stakeholders to understand challenges and translate them into analytical use cases.
• Data Preparation:
  Work with large volumes of structured and unstructured data, ensuring proper data cleaning, transformation, and feature engineering.
• Statistical Analysis:
  Perform statistical modeling, A/B testing, hypothesis testing, and exploratory data analysis (EDA).
• Dashboard Development:
  Design, develop, and maintain interactive dashboards and reports using tools like Power BI.
• Report Development & Automation:
  Design and create interactive and visually appealing reports, dashboards, and data visualizations using tools like Power BI, Alteryx, or similar.
• Ad Hoc Analysis:
  Perform ad hoc data analysis to answer specific business questions and uncover actionable insights.
• Model Development:
  Design, develop, test, and deploy machine learning models for classification, regression, clustering, and forecasting problems.
• Deployment & Monitoring:
  Operationalize models and BI solution into production environments and monitor performance over time.
• Tool Development:
  Create reusable scripts and tools in Python or R to support the data science lifecycle.
• Data Visualization:
  Develop dashboards and reports to present model outputs and KPIs using Power BI, Tableau, or similar tools.
• Model Governance:
  Ensure reproducibility, documentation, version control, and alignment with governance frameworks.
• Innovation:
  Stay up to date with the latest trends and advancements in AI, ML, and data science to bring new ideas into the business.
• Collaboration:
  Work closely with Data Engineering teams to deploy models and ensure data pipelines support model requirements.

Job Specifications:

Education / Certifications:

• Bachelor's or master's degree in data science, Computer Science, Statistics, Mathematics, or related field.
• 2+ years of experience in applied data science, machine learning, or advanced analytics roles.
• Proficiency in SQL and experience working with relational databases.

Job Qualifications:

• Excellent data visualization and storytelling skills
• Experience in Business intelligence reporting tools (e.g., Power BI, Metabase, etc..)
• Experience in data modelling and report development.
• Strong analytical and problem-solving and analytical abilities.
• Effective communication and collaboration skills.
• Excellent storytelling skills with the ability to present complex results to non-technical audiences.
• Ability to work collaboratively in a dynamic, cross-functional environment.
• Strong programming skills in Python or R, with experience in libraries such as Pandas, Scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Solid understanding of supervised and unsupervised learning techniques and statistical modeling.
• Experience with SQL and working knowledge of relational databases (e.g., MSSQL, Oracle, PostgreSQL).
• Familiarity with MLOps practices, model lifecycle management, and cloud platforms.
• Hands-on experience with data visualization tools like Power BI, Tableau, or matplotlib/seaborn.
• Strong analytical thinking and ability to translate business problems into technical solutions.
• Insurance or financial services industry experience is a plus.