Senior Business Intelligence Specialist/Assistant Manager

Overview:

Incumbent will work closely with cross-functional teams to collect, analyze, and interpret large datasets, leveraging predictive modelling to guide data-driven decisions. This position combines a deep understanding of Business Intelligence and Analytics with the ability to build and implement predictive models that address key business questions.

Job Description:

• Predictive Modeling: Develop and apply predictive models to anticipate trends, customer behavior, and other strategic insights, using statistical and machine learning techniques.
• Data Analysis: Analyze structured and unstructured data from various sources to uncover patterns, trends, and insights that inform business strategies.
• Business Intelligence: Build, maintain, and improve business intelligence dashboards and reports that allow stakeholders to access critical data and monitor key performance indicators (KPIs).
• Cross-Functional Collaboration: Partner with teams across the organization, including marketing, finance, and product, to translate data findings into actionable recommendations.
• Data Management: Ensure the integrity, accuracy, and security of data throughout the data lifecycle, and maintain thorough documentation of methodologies and processes.
• Forecasting: Create and support forecasting models to inform business planning and identify opportunities for optimization.
• Insights Communication: Present complex data and predictive insights in clear, concise formats suitable for executive and non-technical stakeholders.
• Process Improvement: Identify opportunities to streamline and enhance data collection, analysis, and reporting processes.
• Automation: Develop and implement scripts or automated processes to improve the efficiency of data workflows, reporting, and model deployment.

Requirements:

• A Bachelor’s degree in Data Science/Statistics/Mathematics/Computer Science or related field.
• Proficiency in building Predictive Models using techniques such as linear regression, logistic regression, decision trees, random forests, clustering, and neural networks is highly preferred.
• Strong proficiency in Python or R for data analysis and modeling; SQL for querying databases; experience with Business Intelligence tools (e.g., Power BI, Tableau).
• Advanced knowledge of statistical analysis, probability, and data mining.
• Understanding of machine learning algorithms and model evaluation techniques, with hands-on experience in model training and tuning.
• Ability to approach complex problems with a strategic, data-driven mindset, identifying trends and insights that drive business outcomes.

Preferred skills to have:

• Experience in cloud-based data platforms (e.g., AWS, databrick) and big data tools (e.g., Spark, Hadoop).
• Knowledge of ETL processes and data warehousing.
• Familiarity with advanced machine learning frameworks such as TensorFlow, Scikit-Learn, or Keras.
• Industry-specific experience in Finance/Fintech or Marketing is preferable.