Senior Data Analyst
Imprescindible:PythonGitCloudFullstackDataAISeniorLeadJunior
Responsibilities:
- Strategic Problem Definition & Analysis Leadership
- Lead the definition and refinement of complex business problems from a technical and strategic data perspective, ensuring alignment with organizational goals and long-term strategic objectives.
- Conduct comprehensive stakeholder analysis to understand underlying business needs and translate them into sophisticated analytical frameworks.
- Advanced Technical Implementation & Development
- An Individual Contributor producing data analysis, calls, and requirements production (SQL, Python, Metabase, PowerBI, etc.) while maintaining world-class technical standards and driving innovation in analytical methodologies
- Architect and implement complex data models, algorithms and analytical frameworks that support enterprise level decision making.
- Stakeholder Management & Strategic Alignment
- Independently drive the alignment of business requirements with executive stakeholders, defining advanced metrics, and architecting comprehensive business intelligence solutions (e.g., interactive dashboards, predictive reports) to fulfill strategic objectives.
- Expertly communicate and make stories out of complex results and strategic insights to diverse stakeholder, including senior leadership, influencing data-driven decision-making across the organization.
- Collaborate strategically with data engineering, development, and product teams to define requirements for advanced analytics & insights tooling, ensuring data infrastructure supports future analytical needs.
- Clearly communicate business requirements and analytical insights to stakeholders, defining scope, deliverables, and potential impacts.
- Proactively define project workstreams and data solutions by directly collaborating with other teams.
- Establish and maintain strong relationship with C-Level Executives to ensure analytical initiatives support business priorities.
- Customer Journey & Business Optimization
- Quantify and analyze all elements of the end-to-end customer journey with a high degree of precision, identifying significant opportunities for conversion, engagement, and retention, and proposing strategic interventions.
- Develop models and predictive analytics to support personalized marketing and product development strategies.
- Generate impactful business insights and formulate strategic, data-backed recommendations that drive measurable business outcomes.
- Technical Excellence & Data Infrastructure Leadership
- Perform and track complex data extraction, rigorous data cleaning, and advanced transformations independently, often designing and implementing robust data pipelines.
- Produce sophisticated dashboards, reports, and analytics independently.
- Proactively understand, ensure, and govern data quality across various datasets. Troubleshot complex data quality issues, identifying root causes and proposing robust, scalable improvement suggestions.
- Define problems and propose solutions based on experience and active listening.
- Team Leadership
- Guide junior data analysts, providing technical expertise, best practices, and fostering their professional development.
- Establish performance standards and quality metrics for analytical work across the team.
- Lead technical training initiatives and knowledge sharing sessions to elevate the analytical capabilities of the entire team.
Profile:
- At least a bachelor’s degree in a quantitative discipline (e.g., Mathematics, Statistics, Computer Science, Economics) or a closely related field. A master's degree is a bonus.
- At least 5+ years of progressive experience as a Data Analyst or in a similar quantitative, analytical role, demonstrating increasing responsibility and complexity of projects.
- Advanced coursework or professional development in statistics, machine learning, business intelligence, or related analytical disciplines.
- Demonstrated expertise in product analytics, including defining, tracking, and interpreting key performance indicators (KPIs) and user behavior metrics to drive product strategy.
- Proven track record of leading high-impact analytical projects that have influenced strategic business decisions
- Expertise in experimental design and A/B testing methodologies with statistical significance assessment.
- Proactively identify, thoroughly troubleshoot, and independently provide robust and scalable solutions to complex data quality issues across diverse datasets.
- Proven ability to resolve data conflicts and discrepancies that impact multiple business units
- Expert in performing advanced Exploratory Data Analysis (EDA), identifying patterns, anomalies, and correlations, and translating these into actionable business insights.
- Advanced expertise in statistical modeling, predictive analytics, and machine learning applications for business problems.
Hard Skills:
- Advanced-to-Expert Level skills in fullstack Data Skills: with at least one skill to a world-class level.
- SQL (Structured Query Language): Expert
- Microsoft Excel: Expert
- BI Tools (e.g., PowerBI, Metabase): Expert
- Python or R (for data analysis): High to Expert
- Data Cleaning and Preparation: Expert
- Exploratory Data Analysis (EDA): Expert
- Statistical Concepts: High
- Marketing Analytics Tools (Google Analytics, Whatsapp, etc.): High
- Version Control (e.g., Git/GitHub/GitLab): High
- AI/ML Application (Analytical Focus): Medium to High
- Data Warehousing/Cloud Data Platforms: High
- API Integration for Data: Medium