Senior Manager-Data Science

Key Responsibilities:

Leadership and Team Management:

- Lead, mentor, and develop a team of data scientists.
- Foster a culture of innovation, collaboration, and continuous learning.
- Set clear goals and performance expectations for the team.

Strategy and Vision:

- Define and implement the data science strategy aligned with the company’s objectives.
- Identify and prioritize data science projects that drive business value.
- Stay abreast of industry trends and emerging technologies to keep the organization at the forefront of data science.

Technical Expertise:

- Oversee the development and deployment of machine learning models and algorithms.
- Ensure best practices in data modeling, coding, and experimental design.
- Provide technical guidance on complex data science projects.

Collaboration and Communication:

- Work closely with business leaders to understand their needs and translate them into data science initiatives.
- Communicate findings and recommendations to both technical and non-technical stakeholders.
- Collaborate with data engineering, IT, and other departments to ensure data availability and integrity.

Project Management:

- Manage multiple data science projects, ensuring timely and successful delivery.
- Allocate resources effectively and balance team workloads.
- Monitor project progress and make adjustments as needed.

Performance Measurement:

- Develop metrics to measure the impact and effectiveness of data science initiatives.
- Continuously evaluate and refine models and strategies based on performance data.
- Report on key performance indicators to senior management.

Qualifications:

- Education:

- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Master’s or Ph.D. preferred.

- Experience:

- 7+ years of experience in data science or a related field.
- 3+ years in a leadership or managerial role within a data science team.
- Proven track record of delivering impactful data science solutions in a business context.
- Technical

Skills:

- Expertise in statistical analysis, machine learning, and predictive modeling.
- Proficiency in programming languages such as Python, R, or SQL.

- Experience with data visualization tools like Tableau, Power BI, or similar.
- Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure).

- Soft Skills:

- Strong analytical and problem-solving abilities.
- Excellent communication and presentation skills.
- Ability to translate complex technical concepts into actionable business insights.
- Strong organizational and project management skills.

Preferred Qualifications:

- Experience in [specific industry or domain relevant to the company].
- Knowledge of deep learning, NLP, or other advanced AI techniques.

- Experience with Agile methodologies and project management tools.