Role Profile

The Lead Data Scientist will be responsible for discovering insights from vast amounts of complex data sets and building models to support the business objectives and decision-making. The role holder will provide new insights into the business and utilize advanced statistical analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.

He/she will work as an expert in data manipulation, visualization, building and optimizing classifiers using machine learning and deep-learning-based techniques. The role has no direct reports currently, but the job holder should have the potential of managing a team.

Key Responsibilities:

• Project Identification, Execution and Management: Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Work with the Larger Business Intelligence team in identifying and integrating datasets that can be leveraged for further analytics and work with the Strategy & Data team members to strategize and execute the development of data products. Lead project execution to ensure that data project(s) scope is understood, completed on time and according to service delivery specifications. Conceive, plan, and prioritize data projects in alignment with organizational goals. Translate unstructured problems into well-defined machine learning projects or research.
• Objectively analyse data for trends and patterns, propose analytic solutions and ideas to stakeholders, and implement improvements as needed to operationalize systems and processes. Mine and analyse data from company databases for improvement and optimization of strategic initiatives and operational processes. Execute analytical experiments methodically to help solve business problems and make an impact on strategic initiatives and operational processes.
• Data Preparation and Modelling: Assess the effectiveness and accuracy of new data sources and data-gathering techniques. Undertake cleaning and pre-processing of structured and unstructured data to build and enhance products, processes and systems. e.g. optimization; Smart pricing; Churn prediction analysis; Demand prediction and Market event forecasting. Use diagnostic, predictive, and prescriptive modelling to improve customer experiences and optimize revenue generation as well as other business outcomes. Develop and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
• Stakeholder Management:Establish strong relationships with all stakeholders across the business and ensure work is prioritized according to business needs and opportunities. Collaboratively engage with executive leaders while leading business problem-solving using a broad spectrum of data science tools, packages and visualization techniques.
• Data Analysis: Lead thestandardisation of methods and algorithms used across the business to analyze data. Provide forward-thinking recommendations to the business by building an in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs. Undertake ad-hoc data requests to meet changing business needs.
• Leadership: Develop and lead a team of highly motivated and effective Data scientists in the near future. Manage team performance and create a high-performance culture within the team. Have frequent one-on-one sessions and performance dialogues to ensure delivery of the team’s mandate.
• Documentation: Develop up-to-date documentation of data science projects.

 Minimum Requirements & Key Skills:

• A degree in Statistics, Mathematics, Computer Science, or another quantitative field;
• Relevant professional certificates;
• Minimum of 4 years’ experience in manipulating data sets and building statistical models;
• Programming Skills – knowledge of and experience with Statistical programming languages like R, Python, SQL, Java, Scala, C++, or JavaScript;
• Experience working with and creating data architectures;
• Experience with different machine learning techniques and algorithms (clustering, regression, simulation, scenario analysis, modeling, decision tree learning, artificial neural networks, k-Nearest Neighbors, Naive Bayes, SVM, etc.) and their real-world application;
• Experience in statistical and data mining techniques (text mining, GLM/Regression, Random Forest, social network analysis, Boosting, Trees, etc.);
• Experience visualizing and presenting data for use by stakeholders using Looker Studio or any other visualization tool;
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies;
• Excellent written and verbal communication skills for coordinating across teams and communicating findings to technical and non-technical teams;
• Desire to learn and master new technology skills and techniques;
• Strong problem-solving skills and aptitude;
• Ability to lead a team of Data Scientists;

 Competencies & Skills

• Data analytics;
• Analytical Thinking;
• Problem Solving Skills;
• Strong Project Management Skills;
• Stakeholder Management;
• Detail Orientation.

Role Profile:

We are looking for an individual with an eye for talent. The ideal candidate will be tasked with championing the scouting and retaining the best talent within the technology function from junior to senior leadership levels. He/she will work closely with the tech leadership to enhance staff performance, support employee development, and create strong relationships with all the key stakeholders within the team to ensure delivery of the talent and people agenda. 

Primary Duties & responsibilities:

• Talent Acquisition: Work collaboratively with the technology leadership to  determine the staffing requirements for the tech team to drive the successful implementation technical strategy. Develop and implement various recruitment strategies for the efficient and timely hiring and placement of employees. Provide guidance to the hiring managers on job reviews and lead development of job descriptions for new or revised positions. Manage the end to end recruitment process for technical roles including interview scheduling for the Line Managers and Hiring team members, salary negotiation for successful candidates, background checks and contracting for the selected candidates.
• Talent Management & Retention: Support the technology leadership in determining training needs for their team members, discussing those needs with the people leadership for incorporation to the annual learning and development agenda. Coach the leadership & management  teams on our performance management tool and processes to ensure  best practices in employee performance management and engagement. Work closely with management and employees to improve work relationships, build morale, and increase productivity and retention.
• Stakeholder Management: Establish and maintain good working relationships with the tech leadership and employees. Leverage on the relationships to push the people's agenda within the function and ensure the people's needs are met.
• Business Advisory: Provide guidance and input on the technology business unit restructures, workforce planning and succession planning. Analyzes trends and metrics in partnership with the engineering team to develop solutions, programs and policies. 
• Culture: Direct and support initiatives to drive a positive work environment; promote team innovation and engage teams to identify improved ways of working. Guide the tech leaders on ways to promote open communication, teamwork and facilitating meaningful engagement within the team.
• Reporting: Prepare and present monthly workforce reports as required and analyze the data to develop action plans with leaders to address key issues arising from these reports.   Design, coordinate and provide relevant statistical information, data and reports on recruitment activities, gender analysis, and other applicable recruitment and people metrics.
• Supplier Management: Support the selection of one or more placement agencies to complement the recruitment process should the need arise. Act as the Account Manager for these agencies overseeing the communication between them and the tech leadership. Oversee the contracting, SLA signing and billing with the agencies factoring in the business and technological needs and interests.

Qualifications 

• A minimum of 5 years experience with a minimum of 2 years as a Tech Business Partner or Technical Recruiter supporting the end recruitment cycle and talent management;
• Proven work experience as a Technical Recruiter (either an in-house recruiter or a staffing agency recruiter);
• Degree or Diploma in Human Resources Management;
• HR Generalist background is preferred;
• Thorough understanding of technology, technical roles and technical skills;
• Solid ability to conduct different types of interviews (structured, competency-based, stress etc);
• Hands on experience with various selection processes (video interviewing, phone interviewing, reference check etc);
• Ability to organize skills assessment centers (in tray activities, work samples, psychometric and IQ/EQ tests, etc) is an added advantage
• Hands on experience with recruiting softwares, HR databases, Applicant Tracking Systems (ATS) and Candidate Management Systems (CMS) as well as Human Resource Information Systems (HRIS) or Human Resource Management Systems (HRMS);
• Ability to engage with new people from diverse backgrounds and form meaningful relationships which have a long-lasting impact on our talent pool.
• Demonstrated experience finding innovative and creative solutions to create networks, build relationships and find prospective candidates;
• should have a knack for turning the hiring process, which is known to be boring worldwide, into a fun experience for everyone applying to be part of Kyosk

Desired Competencies

• Business Acumen;
• Stakeholder Management;
• Great networker and a relationship builder;
• Excellent communication and interpersonal skills;
• Attention to detail;
• Focus on Quality;
• Strong decision-making skills;
• Tech Savyy.