Key Responsibilities :
1. Data Preparation & Engineering :
- Extract, clean, transform and process messy, data from various sources to prepare it for analysis and modeling.
- Help to reduce manual effort, improve efficiency, enhance data quality, and ensure the reliable and timely delivery of data for reports and dashboards through automation.
- Supports : The foundational work of a Data Engineer or Analytics Engineer, ensuring data readiness and quality.
2. Business Acumen & Problem Solving :
Translate complex business questions into well-defined data science problem and analytical tasks.Perform rigorous Exploratory Data Analysis (EDA) to understand data characteristics, identify patterns, trends, uncover hidden insights, potential dataquality issues, and formulate hypotheses.Supports : The strategic thinking and analytical rigor of a Data Scientist or highly skilled Data Analyst, bridging the gap between business needs and technical solutions.3. Data Analysis & Insight Generation (Technical) :
Should be able to synthesize large datasets into actionable insights using SQL, Python, DAX, PowerQuery, and statistical tools.Apply appropriate statistical methods, data mining techniques, and machine learning algorithms (where applicable) to address specific business needs (e.g., prediction, classification, clustering, forecasting).Use Large language models (LLMs) to get insights and generate summaries from data by analyzing text and identifying patterns in data.Supports : The core analytical work of a Data Scientist, leveraging a wide array of technical tools and advanced methodologies to extract meaningful intelligence.4. Business Intelligence & Visualization :
Develop and maintain robust data models, interactive dashboards, and reports using BI tool to support real-time decision-making.Ensure visualizations effectively communicate key performance indicators (KPIs), trends, and insights, enabling users to explore data and make data-driven decisions independently.Supports : The responsibilities of a Business Intelligence Developer or Analyst, focusing on making data accessible and understandable for business users.5. Project Management, Leadership & Collaboration :
Manage and lead multiple data projects independently with best practices, ensuring timely delivery of high-impact analytics and ad hoc reporting."Continuously iterate on data models and approaches based on performance feedback and evolving business requirements.Stay up to date with the latest advancements in business intelligence, data science, machine learning, AI, and relevant technologies.Work with data scientists and analytics engineers in the team to integrate AI solutions into existing systems and workflows.Collaborate cross-functionally with the business and internal team.Supports : The leadership, strategic oversight, continuous improvement, and cross-functional communication aspects typically found in a Senior or Lead role within data analytics or data science.Required Skills and Experience :
Min 5+ years of experience in Business Intelligence or Advanced Data AnalyticsBachelor's or Master's degree in Data Science, Statistics, Business Analytics, or a related field.Advanced proficiency in SQL, preferably in Google Big Query to query, clean, manipulate, arrange, and present dataHands-on experience with BI tools, preferably MS Power BIStrong experience in DAX and Power QueryExperience with Python for Advanced Analytics and Large language models (LLMs)Familiarity with cloud computing platforms, preferably Google CloudSkills Required
Ms Power Bi, Power Query, Dax, Python, Sql