Data Analyst - Client Management & Project Coordination

We are seeking a highly skilled and motivated Data Analyst to join our team. The ideal candidate will play a critical role in understanding client requirements, coordinating with the data engineering team, and analyzing complex datasets to extract meaningful insights. This role is essential in facilitating the successful completion of data projects, ensuring data accuracy, and delivering actionable insights that drive business decisions.

#### **Key Responsibilities:**

- **Client Requirement Analysis:**

- Engage with clients to understand their data needs, business goals, and project requirements.

- Translate client requirements into detailed, actionable project specifications.

- Develop a deep understanding of the client's industry and specific challenges to provide tailored data solutions.

- **Project Coordination:**

- Act as a liaison between clients and the data engineering team to ensure alignment and effective communication.

- Coordinate with data engineers to acquire, preprocess, and prepare necessary data.

- Monitor project progress, troubleshoot issues, and ensure timely delivery of milestones.

- Provide regular updates to clients and stakeholders, ensuring transparency and managing expectations.

- **Data Management:**

- Perform data cleaning, transformation, and structuring to prepare datasets for analysis.

- Ensure data quality and integrity by implementing rigorous validation checks and data governance practices.

- Manage data storage, access, and retrieval processes to maintain data security and confidentiality.

- **Data Analysis:**

- Conduct exploratory data analysis to uncover trends, patterns, and anomalies in large and complex datasets.

- Apply statistical methods and advanced analytical techniques to interpret data and generate insights.

- Develop predictive models and conduct hypothesis testing to support decision-making.

- Create and maintain dashboards, visualizations, and reports to present findings in a clear and actionable manner.

- **Technical Skills:**

- Proficient in Microsoft Excel for data manipulation, analysis, and visualization.

- Strong programming skills in Python, including experience with data analysis libraries such as Pandas, NumPy, Matplotlib, and Seaborn.

- Familiarity with SQL for querying relational databases and managing large datasets.

- Experience with data visualization tools such as Tableau, Power BI, or similar platforms.

- **Cross-Domain Knowledge:**

- Ability to apply data analysis techniques across various domains and industries, adapting methodologies to specific contexts.

- Stay updated with the latest trends, tools, and best practices in data analytics, machine learning, and data science.

- Collaborate with subject matter experts to enhance domain-specific insights and solutions.

- **Process Improvement:**

- Identify opportunities for process optimization and automation within data projects.

- Develop and implement best practices for data analysis, reporting, and project management.

- Contribute to the continuous improvement of data services by providing feedback and suggestions.

#### **Qualifications:**

- Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. A Master's degree is a plus.

- 1+ years of experience in data analysis, business intelligence, or a related role.

- Strong analytical, problem-solving, and critical-thinking skills.

- Excellent communication, presentation, and interpersonal skills.

- Ability to work independently and as part of a collaborative team.

- Proven experience in managing multiple projects simultaneously and meeting deadlines.

#### **Optional but Preferred Skills:**

- Experience with machine learning techniques and algorithms.

- Familiarity with big data technologies (e.g., Hadoop, Spark).

- Knowledge of data warehousing concepts and tools.

- Understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud).

#### **What We Offer:**

- Competitive salary and benefits package.

- Opportunities for professional growth and development.

- A collaborative and supportive work environment.

- The chance to work on diverse and exciting data projects.

- Access to the latest tools and technologies in the field of data analytics.