Principal Data Scientist

Job Description: Principal Data Scientist

Responsibilities:

1. Lead and manage complex data science projects from inception to completion, ensuring timely delivery and high-quality results.

2. Collaborate with stakeholders to identify business problems, define project objectives, and establish success criteria.

3. Develop and implement advanced statistical models, machine learning algorithms, and predictive analytics to solve complex business problems.

4. Analyze large and complex datasets to extract actionable insights, facilitating data-driven decision-making.

5. Design and optimize data pipelines and workflows for efficient data collection, preparation, and analysis.

6. Apply data visualization techniques to effectively communicate analytical findings to non-technical stakeholders.

7. Provide strategic guidance and thought leadership in the application of data science and advanced analytics.

8. Mentor and provide technical leadership to data science teams, fostering a culture of innovation and continuous learning.

9. Stay updated with emerging technologies, algorithms, and trends in data science, machine learning, and AI.

10. Collaborate with cross-functional teams to integrate data science solutions into production systems and processes.

11. Collaborate with business units and executives to define and drive the data science strategy and roadmap.

12. Evaluate and recommend appropriate tools, platforms, and technologies to enhance the organization's data science capabilities.

13. Promote and advocate for the use of ethical and responsible data science practices.

14. Contribute to research and development initiatives to advance the field of data science within the organization.

15. Provide guidance and support in data acquisition, data quality management, and data governance.

16. Represent the organization at industry conferences and events to showcase data science capabilities and expertise.

Requirements:

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

- Extensive experience as a Data Scientist, with a track record of leading and delivering complex data science projects.

- Strong expertise in statistical analysis, machine learning algorithms, and predictive modeling.

- Proficiency in programming languages such as Python or R.

- Experience with data visualization tools and techniques.

- Strong knowledge of data manipulation, data cleaning, and feature engineering.

- Excellent understanding of statistical techniques and methodologies.

- Solid understanding of big data technologies and distributed computing frameworks.

- Experience with cloud platforms and services for scalable data processing and model deployment.

- Strong leadership and mentoring skills, with the ability to inspire and guide data science teams.

- Excellent communication and presentation skills to convey complex concepts to both technical and non-technical stakeholders.

- Strong business acumen and the ability to translate business problems into data science solutions.

- Strategic thinking and the ability to drive innovation and continuous improvement in data science methodologies.

- Proven ability to work collaboratively with cross-functional teams and stakeholders at all levels of the organization.

- Strong project management skills to handle multiple projects and prioritize tasks effectively.

- Experience in industries such as finance, healthcare, retail, or manufacturing is beneficial.

- Contributions to the data science community, such as publications, patents, or conference presentations, are a plus.