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Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether youâve got deep experience in commercial real estate, skilled trades or technology, or youâre looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Â
Key Responsibilities:
We are seeking a detail-oriented and analytical Data Analyst to join our team. This role is responsible for collecting, organizing, and analyzing large datasets to uncover actionable insights that drive business decisions. The ideal candidate will combine strong technical skills with excellent communication abilities to translate complex data into clear visualizations and recommendations for stakeholders at all organizational levels.
Data Analysis
Collect, organize, and analyze large datasets from multiple sources to identify trends, patterns, correlations, and business opportunities. Develop and maintain databases, spreadsheets, and data systems to ensure data accuracy, consistency, and integrity across the organization. Conduct statistical analysis, data modeling, and predictive analytics to extract meaningful insights and data-driven recommendations. Perform exploratory data analysis to understand data characteristics, distributions, and relationships between variables. Apply advanced analytical techniques to solve complex business problems and support strategic decision-making.
Data Visualization
Design and develop comprehensive reports, interactive dashboards, and visualizations using Power BI and Tableau to effectively communicate findings to stakeholders. Create executive-level presentations and summaries that translate technical analysis into clear, actionable business insights. Ensure all visualizations are clear, concise, intuitive, and tailored to the audience's level of technical understanding. Implement data visualization best practices including appropriate chart selection, color schemes, and user experience design. Build automated reporting solutions that provide real-time visibility into business performance and key metrics.
Business Intelligence
Develop and maintain business intelligence reports and dashboards to track key performance indicators (KPIs), metrics, and operational performance. Analyze data to identify areas for improvement, operational inefficiencies, and opportunities for business growth and optimization. Monitor business trends and provide proactive insights that inform strategic planning and resource allocation. Support forecasting, budgeting, and planning processes through data-driven analysis and scenario modeling. Collaborate with business units to define metrics, establish benchmarks, and measure progress toward organizational goals.
Stakeholder Communication & Collaboration
Present findings, insights, and recommendations to stakeholders including executive leadership, department heads, and cross-functional teams through compelling presentations and reports. Collaborate with stakeholders across the organization to identify data needs, understand business requirements, and develop analytical solutions that address specific challenges. Translate business questions into analytical frameworks and communicate technical concepts in business-friendly language. Facilitate data-driven discussions and provide consultation on analytical approaches and interpretation of results. Build strong relationships with business partners to ensure analytics deliverables align with strategic priorities.
Tools and Technologies
Develop and maintain expertise in a comprehensive range of data analysis tools and technologies including Power BI, Tableau, Excel, SQL, Python (Pandas, NumPy), and R. Leverage Python and R for advanced statistical analysis, data manipulation, and automation of analytical workflows. Utilize SQL to extract, transform, and analyze data from relational databases including MySQL, PostgreSQL, and MongoDB. Create complex Excel models and analyses using advanced functions, pivot tables, Power Query, and VBA when appropriate. Stay current with emerging tools, technologies, and analytical methodologies to continuously enhance analytical capabilities and efficiency.
Quality Assurance & Data Governance
Ensure data accuracy, completeness, consistency, and integrity by implementing rigorous quality control measures and validation procedures. Perform data cleaning, transformation, and standardization to prepare datasets for analysis and ensure reliable outputs. Identify and address data quality issues promptly through root cause analysis and implementation of corrective measures. Document data sources, analytical methodologies, assumptions, and processes to ensure reproducibility and knowledge transfer. Establish and maintain data governance standards including naming conventions, version control, and access management. Conduct regular audits of data systems and analytical outputs to maintain high quality standards.
Education & Certifications
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Business Analytics, Economics, or related quantitative field. Data Analysis certification required (examples: Microsoft Certified: Data Analyst Associate, Google Data Analytics Certificate, IBM Data Analyst Professional Certificate, or equivalent recognized certification).
Technical Skills - Required
Power BI Expertise: Advanced proficiency in Microsoft Power BI including dashboard creation, DAX calculations, Power Query, data modeling, and interactive report design. Ability to build professional dashboards with complex visualizations that meet business requirements.
Programming & Statistical Analysis: Strong proficiency in Python with Pandas and NumPy for data manipulation, cleaning, and analysis, OR equivalent proficiency in R for statistical computing and data visualization. Ability to write clean, efficient, well-documented code.
SQL Mastery: Advanced SQL skills for querying, joining, aggregating, and manipulating data across relational databases. Experience writing complex queries including subqueries, Common Table Expressions (CTEs), window functions, and optimization techniques.
Excel Proficiency: Advanced Excel capabilities including pivot tables, VLOOKUP/XLOOKUP, INDEX-MATCH, array formulas, Power Query, Power Pivot, and advanced data analysis functions.
Database Management: Working experience with database management systems including MySQL, PostgreSQL, and MongoDB. Understanding of database structures, data relationships, and query optimization.
Data Visualization Tools: Proficiency in both Tableau and Power BI for creating compelling, interactive visualizations and dashboards. Knowledge of visualization design principles and best practices.
Core Competencies
Analytical Excellence: Strong analytical and problem-solving abilities with capacity to work with large, complex datasets and extract meaningful insights. Demonstrated expertise in statistical analysis, hypothesis testing, and data modeling.
Data Quality & Integrity: Meticulous attention to detail with commitment to data accuracy and quality assurance. Systematic approach to validation and error detection.
Critical Thinking: Ability to approach business problems analytically, question assumptions, and develop innovative data-driven solutions. Capacity to evaluate multiple approaches and select optimal methodologies.
Communication Skills: Exceptional ability to communicate complex data insights clearly and effectively to both technical and non-technical audiences. Strong presentation skills with experience creating executive-level reports and visualizations.
Business Acumen: Understanding of business operations, key performance indicators, and how data analysis impacts organizational objectives. Ability to contextualize analysis within business frameworks.
Collaboration: Proven ability to work effectively with cross-functional teams and build productive relationships with stakeholders at all levels. Demonstrated success in understanding and meeting diverse business needs.
Time Management: Strong organizational skills with ability to manage multiple projects simultaneously, prioritize effectively, and meet deadlines in a fast-paced environment.
Master's degree in a quantitative field or MBA with analytics concentration. Additional certifications in SQL, Python, Tableau, or advanced statistical methods. Experience with cloud platforms (Microsoft Azure, AWS, Google Cloud) and big data technologies. Knowledge of machine learning algorithms and predictive modeling techniques. Familiarity with ETL tools (Alteryx, SSIS) and data integration platforms. Experience with version control systems (Git) and agile project management methodologies. Background in specific industries such as finance, marketing, healthcare, retail, or operations. Experience mentoring junior analysts or leading analytical initiatives.
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