Piper Companies is seeking a
Data Analyst to join an established
Investment Management company located in
Wayne, PA . This position is
HYBRID, and requires you to be onsite Monday, Tuesday, Wednesday. The
Data Analyst will be responsible for supporting an enterprise data warehouse, leveraging technical expertise to improve processes and provide actionable insights.
Responsibilities for the Data Analyst: - Data Management: Manage data validation queue and monitor data exceptions.
- Analysis & Reporting: Collect, analyze, and interpret data to identify trends and develop dashboards to track KPIs.
- Collaboration: Work with business partners to understand data needs and support strategic initiatives.
- Quality Assurance: Ensure data accuracy through regular audits and validation.
Qualifications for the Data Analyst: - 3-5 years of experience as a Data Analyst, preferably in finance.
- Bachelor's degree in Finance, Economics, Mathematics, Data Science, or Computer Science.
- Proficiency in data analysis tools like Excel, SQL, Tableau, or Power BI.
- Strong analytical and problem-solving skills.
- Excellent communication skills with a customer-centric focus.
- Ability to work independently and as part of a team.
- Attention to detail and commitment to data accuracy.
- Comfortable working in a fast-paced, high-impact environment.
- Experience with CRM systems (e.g., Salesforce).
- Knowledge of financial products and services.
- Advanced statistical analysis skills.
Compensation for the IT Consultant: Salary: $80,000-$110,000 based on experience
Comprehensive Benefits Medical, Dental, Vision, 401K, PTO, Sick Leave if required by law
This job opens for applications on April 4th, 2025 . Applications for this job will be accepted for at least 30 days from the posting date. Technologies and tools relevant to this role are SQL, Python, R, Microsoft Excel, Tableau, Power BI, Apache Hadoop, Apache Spark, Jupyter Notebook, SAS, and Google Cloud AutoML. Important skills and concepts include data analysis, data visualization, statistical analysis, predictive analytics, data mining, machine learning, data cleaning, report writing, dashboard development, data warehousing, ETL processes, and regression analysis.