of Senior Data Analyst- Financial Services

Company Description

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.

Why Join The Sia Team?

Excellence | Entrepreneurship | Innovation | Teamwork | Care & Support | Employee Wellbeing

These are the six core values that guide all our actions. As an expression of our values, our Sia team concept describes our commitment to fostering a sense of community within and among our offices. We believe that knowledge sharing is the key, not only to innovation, but to the growth and development of our people.

Your experience at Sia will be enriched by a(n):  

• Entrepreneurial journey
• Career advocacy program that supports achieving professional development goals through guidance, and real-time feedback
• Continuous learning & development opportunities
• Diversity, equity, and inclusion programs with an ever-growing list of global affinity initiatives

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, or Salesforce 
  • ETL Tools: dbt, Airflow, StreamSets, NIFI, or Kafka or similar 
  • Cloud Platforms: Azure, AWS, GCP, Oracle, or IBM 
  • Source Control: Git or GitHub/Gitlab compatible platforms 
  • Machine Learning Models: Regression, Decision Trees, Neural Nets, or similar 
  • Basic understanding of statistical concepts such as hypothesis testing and probability (Bayesian) preferred 
  • Strong experience with data visualization tools like Tableau, Power BI, or Looker. 
  • Experience with programming languages such as Python or R for data analysis. Libraries like Pandas, NumPy, scikit-learn. 
  • Familiarity with statistical software packages like SPSS, or SAS is a plus. 
  • Experience with data warehousing concepts and technologies. 
• Analytical Skills:  
  • Strong analytical and problem-solving skills. 
  • Ability to think critically and draw meaningful conclusions from data. 
  • Solid understanding of statistical concepts and methods. 
• Communication Skills:  
  • Excellent written and verbal communication skills. 
  • Ability to present complex information clearly and persuasively. 
  • Proven ability to be a great teammate. 
• Industry sector experiences: 
  • Strong preference for experience in financial services including banking, brokerage, insurance, and capital markets 
• Alignment with Sia’s Core Values:  
  • Excellence, Entrepreneurship, Innovation, Teamwork, Care & Support, Employee Well-Being 

Additional Information

Compensation & Benefits 

• Salary + Annual Discretionary Bonus
• Healthcare coverage that includes medical, dental, vision and life insurance policies
• Generous time off 
• Parental leave paid at 100% of base pay for all new parents regardless of gender 
• Building Healthy Families Program
• 9 Company Holidays + 1 Floating Holiday 
• 401(k) Plan - 4% matching on day 1
• College save-up plan & college loan repayment plan
• Monthly cell phone stipend 
• Commuter Benefits 
• Gym Reimbursement through firm medical plan

Our Commitment To Diversity

At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information. 

Hybrid Workplace Guidelines

Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco are expected to live within a reasonable commuting distance and attend the office at least three days per week. For applicants in other markets, including those without a local office, we offer more flexible in-person requirements to accommodate your location. 

Work Authorization & Sponsorship 

At this time, Sia does not intend to pursue employment with applicants who will require now or in the future visa by our company for work authorization in the United States (i.e., H1-B visa, F-1 visa (OPT), TN visa, or any other non-immigrant status).  

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.