The Business Intelligence (BI) Manager is responsible for overseeing the creation and maintenance of data-driven insights that help the organization make better decisions. The role requires gathering, cleansing, organizing, and analyzing large amounts of data in order to generate reports and other visualizations that inform business strategy.
Success in this role demands proven communication skills, problem-solving skills, and knowledge of best practices to guide teams on issues related to the design, development, and deployment of information and reports.
Duties and Responsibilities
Determine customer lifecycle and value (CLV) to the organization
• Integrate internal/external customer level data to measure/track customer value and buying behavior
• Predict and prevent churn by doing a health check analysis of the merchant partners through usage (e.g. recency, frequency of log-ins, most used modules) and transactional data (e.g. GMV, basket size, new vs. repeat customers)
• Lead qualitative insighting programs that supplement the quantitative data gathered through multiple customer touch points to enable data- driven design decisions
● Maintain company performance metric dashboards to ground targets and campaigns
• Keep a record of internal (historical) and external (industry, regional, global) benchmarks for performance comparison
• Perform assessment on all reporting requirements and develop long-term strategies for various reports
• Support cross-functional teams in building and maintaining accurate and credible databases which funnel into the overall company performance reports
● Data Mining, Insighting, and Reporting
• Develop data models, algorithms, and models to address specific business needs
• Use statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics effort
• Prepare reports for executive leadership that effectively communicate trends, patterns, and insights found across multiple data sources
• Collaborate with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance
Qualifications
• Bachelor's Degree in Business Administration or Management, Data Science, Computer Science, or any related field
• At least 3 years of professional experience, preferably in Data Science, Analytics, and Visualization
• Preferably with experience in SaaS and eCommerce
Nice-to-have Experience
• Familiar with Product Design concepts
• Experience with developing machine learning solutions and evaluation metrics
• Proficiency in additional programming languages, particularly Pyspark, R, C++, Javascript and Java
• Familiarity in web and app analytics tools and metrics
• Proficiency in AWS Cloud Services, particularly AWS Glue, AWS Lake Formation
• Familiarity in machine learning tools is a plus (any of scikit-learn, caret, MATLAB, Julia)
Skills & Knowledge:
• Technical expertise in data modeling , database design development, data mining, and
segmentation techniques
• Strong knowledge of and experience with reporting packages (e.g. Business Objects), databases (e.g. SQL, and programming (e.g. Python, R)
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Adept at composing queries, report writing, and presenting findings
• Strong communication skills to effectively convey pertinent data and insights to both technical and/or business minded audiences
• Proficiency in data manipulation tools(any of pandas, dplyr, spark)
• Experience with Extract, Transform, and Load (ETL processes)
• Proficiency in business intelligence tools (any of Tableau, PowerBI, Quicksight, Google Data Studio)
• Proficiency in data visualization packages (any of Dash, Plotly, Matplotlib, Ggplot, Folium)
• Proficiency in SQL and noSQL query languages
• Experience with any big data storage and processing solutions (SQL variants, MongoDB, Spark, Hive, Snowflake, Redshift, etc.)
• Experience with any cloud service or server-based data processing