We are searching for an experienced Senior Data Scientist to join us in driving significance together.
Primary Duties and Responsibilities:
The Data Scientists is responsible for vast amount of data and to optimize business results. The employee will exercise their knowledge of descriptive and multivariate statistical techniques and applications, and database analysis tools and techniques to develop strategic insights to drive business goals.
Required Qualifications:
Tertiary degree, diploma or certificate in a related field (BSc Computer Science, B.IT or Informatics related degrees).
Experience and Knowledge:
- 8-10 + years’ working experience as a Data Scientist or Data Analyst
- Experience in data mining
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Experience in leading and mentoring a team
- Experience with very large datasets a must.
- Extensive experience solving analytical problems using quantitative approaches.
Key Responsibilities:
- Work with cross departmental team to define metrics, guidelines, and strategies for effective use of algorithms and data
- Work closely with statisticians to identify, design, and build appropriate datasets for complex experiments
- Create data mining and analytics architectures, coding standards, statistical reporting, and data analysis methodologies
- Establish links across existing data sources and find new, interesting mash-ups
- Coordinate data resource requirements between analytics team and engineering teams
- Work with product managers, engineers, and analytics team members to translate prototypes into production
- Assist in the development of data management policies and procedures.
- Develop best practices for analytics instrumentation and experimentation.
- Conduct research and make recommendations on big data infrastructure, database technologies, analytics tools, services, protocols, and standards in support of procurement and development efforts
- Drive the collection of new data and the refinement of existing data sources
- Develop algorithms and predictive models to solve critical business problems
- Develop tools and libraries that will help analytics team members more efficiently interface with huge amounts of data
- Analyze large, noisy datasets and identify meaningful patterns that provide actionable results
- Develop and automate new enhanced imputation algorithms
- Create informative visualizations that intuitively display large amounts of data and/or complex relationships
- Provide and apply quality assurance best practices for data science services across the organization
- Develop, implement, and maintain change control and testing processes for modifications to algorithms and data analytics
- Collaborate with database and disaster recovery administrators to ensure effective protection and integrity of data assets
- Manage and/or provide guidance to junior members of the analytics team
Competencies:
- Critical Thinking: Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
- Active Learning: Understanding the implications of new information for both current and future problem-solving and decision-making.
- Systems Analysis: Determining how a system should work and how changes in conditions, operations, and the environment will affect outcomes.
- Complex Problem Solving: Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.
- Deductive Reasoning: The ability to apply general rules to specific problems to produce answers that make sense.
- Inductive Reasoning: The ability to combine pieces of information to form general rules or conclusions (includes finding a relationship among seemingly unrelated events).
- Excellent communication skills: Ability to engage with C-level stakeholders, both verbal and non-verbal and communicate a deep understanding of the business and a broad knowledge of technology and applications.
- Technical Literacy: Possess a high level of technical literacy, which helps them determine how a software solution fits into an organization’s current structure and assists in the development of specifications and requirements.
- Analytical Assessment: A high level of analysis to examine current systems and determine overall project needs and scope.
- Schedule Management: Extensive time management skills to determine development schedules and milestones and ensure that deliverables are completed on time for oneself and your team.
- Team Leadership: To oversee and direct development teams throughout the project development lifecycle, experience with team leadership and motivation is essential.
Ability to translate strategy and strategic objectives into measurable and executable projects. - Experience working on large project(s) incorporating processes and procedures and standards.
Culture and Values:
- We seek understanding.
- We make a difference.
- We’ve got your back.
- We are leaders.
- We are reliable.
- We are brave.