Techno-Functional Lead - Data Science Projects (8-10 yrs)

Job Description :

This role requires a highly motivated and experienced individual to lead and manage data science projects from inception to completion.

The Techno Functional Lead will be responsible for all aspects of the project lifecycle, including planning, execution, monitoring, and control.

This role requires strong technical expertise in data science methodologies, as well as excellent communication, leadership, and project management skills.

Project Management :

- Define project objectives, scope, deliverables, and timelines in collaboration with stakeholders.

- Develop detailed project plans, including resource allocation, milestones, and risk management strategies.

- Track project progress, identify and mitigate potential roadblocks, and ensure timely completion of deliverables.

Resource Management :

- Coordinate with data scientists, data engineers, analysts, and other relevant team members to allocate resources effectively.

- Ensure that team members have the necessary tools and support to complete their tasks.

- Mentor and guide junior team members on best practices in data science and project execution.

Timeline and Budget Management :

- Monitor project timelines and ensure adherence to schedules.

- Manage project budgets and ensure that expenditures are within approved limits.

Stakeholder Communication :

- Act as the primary point of contact between the data science team and business stakeholders.

- Ensure clear and ongoing communication regarding project status, challenges, and results.

- Present project findings and insights to stakeholders in a clear, concise, and impactful manner.

Quality Control :

- Ensure that data science deliverables meet quality standards and business requirements.

- Review project outputs, including models, algorithms, and analyses, for accuracy and relevance.

- Implement and maintain quality control processes throughout the project lifecycle.

Process Improvement :

- Implement best practices for project management within the data science CoE.

- Continuously improve project management processes based on feedback and lessons learned.

Technical Competency :

- Ability to communicate technical concepts and requirements effectively with the data science team.

- Experience in implementing end-to-end advanced analytical solutions.

- Strong understanding of data science methodologies, including machine learning, deep learning, statistical modeling, and data mining.

- Proficiency in data analysis and visualization tools.

Negotiation and Conflict Resolution :

- Mediate conflicts and negotiate solutions that satisfy all parties involved.

- Handle stakeholder expectations and resolve disagreements diplomatically.

Required Skills :

- Project Management : PMP, Agile methodologies (Scrum, Kanban)

- Data Science : Python, R, SQL, Machine Learning algorithms, Deep Learning frameworks

- Communication : Excellent written and verbal communication, presentation skills

- Leadership : Strong leadership, mentorship, and team management skills

- Analytical & Problem-solving : Strong analytical and problem-solving skills

- Business Acumen : Understanding of business needs and how data science can address them