VP, Data Science
Perx Technologies provides a fully integrated customer engagement and loyalty solution that combines a next-generation SaaS loyalty management system and omni-channel marketing technologies for offline and online engagement. Developed with large B2C businesses and their marketers in mind, the Perx platform enables organisations to create real-time revenue generating customer engagements instead of the traditional back-end marketing tools used for many years. The A.I. enabled platform unifies consumers and business eco-systems into one single view for ease of management and decision-making.
Trusted by some of the largest banks, insurers, telcos and retailers, the Perx Platform is the solution of choice for top regional and global B2C enterprises.
Our enterprise SaaS business is at an inflection point and will experience aggressive growth year over year. Customer Engagement and Marketing Tech is a rapidly evolving space and our customers are looking not just for a platform, but a strategic partnership and thought leadership from solution providers. In short, the opportunity is immense.
We’re a company that understands that product innovation comes from people innovation, and that’s why we invest in cultivating leaders and HIPOs throughout the organization. If you’re passionate about creating and contributing to a top-notch culture and talent pool, join us!
The Vice President, Data Scientist manages a team of data engineers and scientists within Perx Technologies to drive value for the business by leveraging on AI and machine learning. Work with product and engineering teams to define the problem statement and develop solution with advanced analytic techniques to address key business challenges. The role will champion and project lead the implementation of the Analytic Data technology stack and associated Data Models, Integration Patterns, Quality Frameworks and Governance Models to achieve the highest revenue and business decisioning outcome for large B2C enterprises while creating personalised and relevant engagements for a positive customer experience.
- Lead, guide, and manage the team of experienced data scientists and be accountable for the team’s delivery of data science projects that drive value for business
- Partner with business stakeholders to understand needs and identify opportunities to apply data science.
- Evaluate, recommend, architect and build big data platform(s) solutions understanding the business needs.
- Oversee the process of data exploration & preparation, the conduct of experiments, review of model performance, and presentation of results to business stakeholders for their feedback
- Lead the presentation of key insights to management with actionable recommendations
- Manage the team to facilitate deployment of finalised solutions to production environment
- Lead the design, reviewing, implementing and analyzing of algorithms that will substantially impact the company’s understanding of its data
- Mentoring and managing junior members of the team as it grows, fostering talent development for the continued growth of the technology team in general.
- Work with the Chief Technology Officer, CEO and Product Manager to answer key questions and projects that will transform the business.
- Assist with the development skill set of a multi-disciplinary team to evolve from statistical services to key decision influencers
Expected Areas of Competence:
- Experience working with enterprise level data for multi-national companies in a hands-on role that will influence and shape how data is acquired, stored, integrated, transformed and consumed for all channels of the business and primarily the enterprise platform offering
- Experience building and managing Big Data SQL Database like MemSQL or Vertica and NoSQL Database like Cassandra or HBase, both a plus
- Direct experience with working within a modern engineering environment (Linux system architecture, Java (MapReduce), Python, PostGreSQL, multithreaded programming, Hadoop, etc)
- Experience with large-scale algorithm challenges pulling data from multiple, complex data sets and implementing solutions on AWS or similar hosting cloud services
- Possess strong Project Management skills to help in the successful guidance and direction to other team members whilst working hands-on delivering and implementation of data architecture solutions and ensuring stakeholder satisfaction.
- Possess complete expertise in your area of technical domain and act as a SME while working closely with other stakeholders within the Technology team.
- Demonstrated experience in architecting, building and maintaining big data platform / store to support enterprise level Analytic projects.
- Proven experience in creating, building and implementing data fabric, dictionaries, data quality and governance frameworks (open source frameworks like Puppet or Chef for deployment and configuration management is a plus)
- Hands-on experience with ‘Big Data’, data mining and predictive analytics
- Deep knowledge of traditional data structure, database design, data warehouses, and Operational data stores
- Hands-on experience with sourcing & architecting suitable EDW solutions (SAS, SAP, EMC, MySQL, SQL Server, Greenplum, Hadoop, MapReduce, HBase, etc)
Education/ Experience Requirements:
- Bachelor’s degree in engineering, IT, Math, Sciences or technical discipline (MSC preferred)
- Candidates will have a minimum 10 years industry experience using acceptable technology and Tools working in a complex systems and development environment building and managing complex products/solutions.
- Ability to quickly prototype experimental solutions and develop robust, maintainable production systems
- Strong results driven personality, with a high level of enthusiasm, energy and confidence
- Ability to demonstrate flexibility and integrity: be able and willing to work hands on, independently or with a small team providing leadership
- Outstanding EQ and stakeholder management skills.
- Ability to make key decisions and deliver results under extremely tight and high-pressure timelines in a highly ambiguous environment.
- Excellent communication skills, both written and verbal, with the ability to interact with cross-functional teams at all levels and in front of enterprise customers.
- Experience, comfort and aptitude interacting with senior management both internally and with clients and partners.
- Must be self-motivated, resourceful, diligent, and adaptive.
- Superior analytical and quantitative skills with a strong understanding of data-driven decisioning and exhibited experience working with Data Science and statistical analysts.
- Strong organizational and project management skills.
On needs basis