Data Scientist - R/Python

Description :

Position Overview : As a Data Scientist, he will be responsible for translating management and business requirements into advanced analytics solutions. He will play a crucial role in the development of data pipelines, business intelligence tools, and the delivery of meaningful insights through trend analysis and business analytics.

Responsibilities :

1. Data Analysis and Modeling :

- Collaborate with cross-functional teams to understand management and business requirements.

- Develop and implement statistical models, machine learning algorithms, and other advanced analytics techniques to derive actionable insights.

2. Data Pipeline Development :

- Design and build efficient data pipelines to support the collection, processing, and analysis of large datasets.

- Ensure the availability, reliability, and scalability of data pipelines to meet business needs.

3. Business Intelligence (BI) Tool Development :

- Work closely with IT teams to develop and maintain BI tools that provide intuitive access to data for business users.

- Create dashboards and reports that visualize key performance indicators and support data-

driven decision-making.

4. Trend Analysis and Reporting :

- Conduct trend analysis to identify patterns, correlations, and anomalies in large datasets.

- Generate and present regular reports on business analytics, highlighting key insights and recommendations.

5. Collaboration and Communication :

- Collaborate with stakeholders to understand their analytical needs and translate them into actionable plans.

- Communicate complex analytical findings to non-technical stakeholders in a clear and concise manner.

Qualifications :

- Master's or Ph.D. in Computer Science, Statistics, Data Science, or a related field.

- Proven experience as a Data Scientist with a focus on business analytics and trend analysis.

- Strong programming skills in languages such as Python or R.

- Experience with data visualization tools (e.g., Zoho Analytics, Tableau, Power BI).

- Knowledge of statistical modeling, machine learning, and data mining techniques.

- Excellent problem-solving and critical-thinking skills.