Job Description

Adelphi Innovation Consulting is dedicated to revolutionizing education through cutting-edge solutions. Our mission is to provide accessible, engaging, and rewarding learning experiences through cutting-edge technology. Technology can bring world-class skills training and recognition to interested learners wherever they may be.

Position Overview:

Adelphi Innovation Consulting is seeking a talented and motivated Data Analyst to join our Data Analytics team. As a Data Analyst, you will play a key role in analyzing, interpreting, and visualizing data to uncover insights, trends, and patterns that inform strategic decision-making and drive business outcomes for our clients. You will work closely with cross-functional teams, including data scientists, business analysts, and consultants, to design and execute data analysis projects that address our clients' needs and objectives. Your analytical skills, attention to detail, and ability to communicate complex findings will contribute to the success and impact of Adelphi's data analytics solutions.

Key Responsibilities:

1. Data Analysis and Interpretation: Analyze and interpret large and complex datasets using statistical and analytical techniques to extract insights, trends, and patterns. Develop data models, algorithms, and visualization techniques to present findings and insights in a clear and actionable manner.

2. Data Visualization and Reporting: Create interactive dashboards, reports, and data visualizations using tools such as Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn). Communicate analytical findings and recommendations to clients and stakeholders through compelling visualizations and presentations.

3. Statistical Analysis and Modeling: Apply statistical techniques, regression analysis, and predictive modeling methods to identify correlations, relationships, and predictive factors in data. Develop predictive models and machine learning algorithms to forecast trends, predict outcomes, and optimize business processes.

4. Data Cleansing and Preparation: Clean, preprocess, and prepare raw data for analysis by identifying and addressing data quality issues, missing values, and outliers. Transform and manipulate data using SQL queries, data wrangling techniques, and scripting languages (e.g., Python, R).

5. Business Insights and Recommendations: Collaborate with business stakeholders and clients to understand their business objectives, requirements, and challenges. Translate business questions into analytical hypotheses, conduct exploratory analysis, and generate actionable insights and recommendations.

6. Data Governance and Compliance: Ensure data integrity, security, and compliance with regulatory requirements (e.g., GDPR, HIPAA) by adhering to data governance policies and best practices. Implement data privacy and security measures to protect sensitive information and mitigate risks.

7. Continuous Learning and Development: Stay current with emerging trends, tools, and technologies in data analytics, machine learning, and data visualization. Participate in training programs, workshops, and industry conferences to expand your skills and knowledge in data analysis and related areas.

Qualifications:

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or related field; Master's degree or professional certifications (e.g., Microsoft Certified Data Analyst, Tableau Desktop Specialist) are a plus.
• Minimum of 3-5 years of experience in data analysis, business intelligence, or related roles, preferably in a consulting or analytics-driven environment.
• Proficiency in data analysis tools and languages, such as SQL, Python, R, or SAS, and data visualization tools (e.g., Tableau, Power BI, QlikView).
• Strong analytical and problem-solving skills, with the ability to analyze complex datasets, derive insights, and make data-driven recommendations.
• Excellent communication, presentation, and storytelling skills, with the ability to communicate technical concepts and findings to non-technical audiences.
• Experience with statistical analysis, hypothesis testing, regression analysis, and machine learning algorithms is preferred.
• Knowledge of data governance, data privacy, and regulatory compliance requirements (e.g., GDPR, HIPAA) is a plus.