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Head of Data Science
4 weeks ago
ROLE: Head of Data Science & Analytics
Reporting Manager: President
Overview:
- He/ She will be leading the global delivery team to build a highly scalable and extensible Analytics/ Data Science/ Data Engineering team that provides the foundation for collecting, storing, modelling, and analysing massive data sets from multiple channels
- The ideal candidate will have demonstrated experience in delivery management, project planning, resource planning, delivery quality, maintain margins and customer satisfaction
- This is a Data analytics & engineering leadership role for a strong leader that loves to operate in trenches with the team
Key Responsibilities:
- A leadership position in the Advanced Analytics and Data Sciences practice
- Responsible for business growth (order booking) and establishing company as a thought leader in the Analytics space
- Build offerings, platforms, solutions and capabilities - to create differentiating position for Company in the market
- Build solutions and capabilities -focusing on leading edge technologies such as AI/ML- collaborating with Company labs.
- Establish and nurture strategic relationships with partners and vendors
- Engage with customers as a thought leader by building and leading an elite pool of architects/specialists/data scientists
- Work with other practices to drive Analytics led transformation of offerings as well as the way we deliver our services and value propositions.
- Manage Presales, Solutioning, Sales Enablement responsibilities for the practice
- As a people manager, build and nurture a talented pool of specialists
- Establish connects with industry stakeholders and manage analyst relationships
Desired Skills & Behaviours:
- High preference for a PhD in one of the following fields from a premier institute:
- Physics, Electrical Engineering, Mathematics, Computer Science, Statistics
- Overall experience of 20+ years. 15+ years of relevant experience in Data Science /Data Analytics Domain
- Experience with implementing data governance models and processes in a large, highly complex business environment for at least 5 years
- In-depth experience of data/information management practices, systems and processes including information lifecycle management, data modelling, master data management, meta-data management
- Cross-industry experience highly preferred. 4+ years of international experience working with Global teams
- 3-5 years of experience as an IT/Technology Head/Leader
- Prior experience in handling portfolio of Enterprise Data Management , Data Science Domain with Latest AI Trends
- Fluent in structured and unstructured data, its management, and modern data transformation methodologies.
- Demonstrated industry experience to:
- Define and create complex models to generate valuable insights from real world data (large, sparse, and noisy datasets)
- Deploy such models into production environments.
- Have a deep and thorough understanding of the latest state-of the art AI technologies. Have a detailed understanding of all main network architectures, deployment modes, data augmentation and preparation, and performance analysis of model architectures
- Excellent communication (written, verbal, and public speaking) as well as time management skills.
- Ability to plan and execute operational and strategic activities.
- Excellent interpersonal & communication skills, including scientific writing, presenting, and formal briefings.
- Ability to evolve with a rapidly changing environment.
- Maintains knowledge of current and emerging technologies.
- Self-directed and responsive to customer expectations.
- Strong analytical and logical problem solving skills.
- Strong interpersonal communication and relational skills, good organizational and project management skills; sound judgment; initiative; flexibility; detail-oriented.
KPI of this Role:
- Grow & Maintain Revenue
- Team development
- Improve Client CSAT
- Maintain Margin
- Define Value of Delivery
Accountability during a Project Lifecycle:
- Fulfilment check during proposal phase
- Margin health
- Feasibility
- Training & Interview prep
- Offshore team onboarding
Day to day Delivery
- Common delivery plan across Data Analytics/ Data Science/ Data Engineering/ Devops/ UI & iteration on delivery plan
- Continuous customer expectation setting
- Delivery quality
- Timeliness of Delivery
- Risk prediction
- Team procurement & replacement
- Renewal & Handoff.
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