1. Data Collection and Integration: Gather and consolidate data from various sources, ensuring data accuracy, integrity, and proper storage. Work with data engineering teams to streamline data collection processes.
2. Data Analysis: Analyze large datasets using advanced statistical and data analysis techniques. Identify trends, patterns, and correlations to derive actionable insights that support business goals.
3. Visualization and Reporting: Create meaningful and visually appealing data visualizations, dashboards, and reports using tools such as Tableau, Power BI, or other relevant platforms. Communicate findings effectively to both technical and non-technical stakeholders.
4. Predictive Modeling: Build predictive models using machine learning and statistical methodologies to forecast outcomes, identify opportunities, and mitigate risks.
5. Business Insights: Collaborate with business teams to understand their goals and challenges. Provide data-driven insights and recommendations to optimize processes, enhance customer experiences, and drive revenue growth.
6. Data Quality Assurance: Ensure data quality and consistency by developing and implementing data validation and cleansing processes. Identify and resolve data quality issues as they arise.
7. Data Governance: Support the development and implementation of data governance practices, ensuring compliance with data privacy regulations and internal data policies.
8. Continuous Improvement: Stay updated with industry trends, emerging technologies, and best practices in data analytics. Propose and implement innovative solutions to enhance the data analytics capabilities of the organization.
9. Cross-Functional Collaboration: Work closely with data engineers, business analysts, and other teams to understand data requirements and ensure smooth data flows across systems.
10. Training and Knowledge Sharing: Train non-technical teams on data interpretation and analysis techniques. Share expertise with colleagues to foster a data-driven culture.

Requirements:

• Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field. Master’s degree preferred.
• Minimum of 3-5 years of experience in data analysis, business intelligence, or related roles.
• Proficiency in data analysis tools such as Python, R, or SQL.
• Experience with data visualization tools (Tableau, Power BI, etc.) for creating meaningful insights.
• Strong knowledge of statistical analysis techniques and predictive modeling.
• Familiarity with machine learning concepts and algorithms is a plus.
• Excellent problem-solving skills with the ability to analyze complex data sets.
• Strong communication skills, both verbal and written, for presenting findings and insights.
• Attention to detail and ability to work independently to meet project deadlines.
• Knowledge of data privacy regulations (e.g., GDPR, HIPAA) and data governance principles.
• Ability to collaborate effectively in a cross-functional team environment.
• Strong analytical and critical thinking skills.

Benefits:

• Competitive salary and opportunities for performance-based bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Retirement savings plan with company contributions.
• Continuous professional development and training opportunities.
• Flexible work arrangements, including remote work options.
• Collaborative and innovative work environment.
• Opportunities for career advancement within a growing data-driven company.