Data Analyst, Senior Consultant- Luxury and Retail

Company Description

About Sia 

Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. 

Sia’s AI & Data Business Unit is the powerhouse of our firm’s innovation—merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia’s AI & Data team, you’ll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. 

Job Description

We are looking to meet talented candidates with at least two years of client-facing consulting experience in information management and business analytics using data to provide meaningful, actionable insights. These insights can help inform the most impactful customer product offers, marketing campaign strategies, servicing optimization, and/or manufacturing and production improvements. 
 
We are especially interested in meeting consultants with a background in Luxury and Retail. 

Key Responsibilities: 

• Data Extraction and Transformation: 
  • Extract data from various sources, including internal databases, data warehouses, ETL Tools and third-party platforms  
  • Clean, transform, and prepare data for analysis, ensuring data quality and consistency. This includes handling missing values, outliers, and inconsistencies. 
  • Develop and maintain ETL (Extract, Transform, Load) processes to automate data workflows. 
  • Develop and maintain post-ETL validation tests 
• Data Analysis and Modeling: 
  • Perform exploratory data analysis (“EDA”) to identify trends, patterns, and anomalies. 
  • Develop and apply statistical methods to analyze data and draw meaningful conclusions - regression analysis, hypothesis testing, etc.  
  • Build and maintain dashboards and reports to track key performance indicators (KPIs) and business metrics. 
  • Use data visualization techniques to effectively communicate insights. 
  • Develop predictive models or forecasting models as needed. 
  • Experience with tools like Tableau or Power BI 
• Data Governance, Security, and Best Practices: 
  • Adhere to data governance and security policies and procedures to ensure data security and privacy. 
  • Maintain data documentation and contribute to the development of data dictionaries and metadata repositories. 
  • Stay up to date with industry best practices and emerging trends in data analysis. 
  • Understand and comply with GDPR/CCPA and data privacy, retention, and confidentiality policies.
• Communication and Collaboration:  
  • Present findings and recommendations to stakeholders at all levels of the organization, including senior management. 
  • Translate complex technical concepts into clear and concise language for non-technical audiences. 
  • Collaborate effectively with cross-functional teams – product managers, engineers, marketing managers – to understand business needs and provide data-driven solutions. 
  • Mentor and guide more junior analysts, providing technical expertise and support.

Qualifications

• Education: Bachelor's or master's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Data Science, or a related area. 
• Experience: 5+ years of experience in a data analysis role, with a proven track record of delivering actionable insights, and 2 or more years client facing consulting experience. 
• Technical Skills:  
  • Proficiency in SQL is essential. 
  • Familiarity with current data platforms: 
  • Databases: SQL Server, Oracle, PostgreSQL, DB2, or MySQL 
  • Data warehouses: Snowflake, Data Bricks, Redshift, or BigQuery 
  • APIs and Datasets: MS Dynamics, Oracle CRM