Data Scientist
Description
COMPANY DESCRIPTION
We are the world’s largest performance marketing network, with over 3,000 experts in 68 offices in 48 markets. We offer a complete suite of crafts designed to deliver customer-centric performance marketing solutions. Armed with intelligent insights and an audience first approach our team of expert consultants deliver integrated media, data and technology solutions that help brands better connect with consumers at every stage of their digital marketing transformation.
In MENA, Kinesso are the Digital Marketing Transformation experts and provide services focused on delivering marketing efficiencies and return of investment for brands across the MENA region.
ROLE OVERVIEW
At Kinesso, we rely on powerfully insightful data to help brands better connect with their consumers at every stage of their marketing transformation.
Our data science team has mathematical and statistical expertise, natural curiosity, and a creative mind that’s not so easy to find. As a data scientist you mine, interpret, and clean data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. And will “slice and dice” data using your own methods, creating new visions for the future.
OBJECTIVES
- Collaborate with advertiser’s brand team and media agencies to develop an understanding of needs.
- Research and devise innovative statistical models for data analysis.
- Communicate findings and insights effectively to both technical and non-technical stakeholders through reports, presentations, and visualizations..
- Enable smarter business processes—and implement analytics for meaningful insights.
- Become a thought leader on the value of data by finding new features or products by unlocking the value of data.
- Develop and implement machine learning models and algorithms to solve complex business problems.
- Stay up-to-date with the latest advancements in data science, machine learning, and AI technologies.
- Work with product and engineering teams to integrate data science solutions into production systems
- Collaborate with data engineers to design and optimize data pipelines and architectures.
- Keep current with technology and industry developments.
RESPONSIBILITIES
- Analyse data for trends and patterns using machine learning algorithms and Interpret data with a clear objective in mind.
- Identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the team to strategize and execute the development of data products.
- Conduct exploratory data analysis to identify trends, patterns, and opportunities for improvement.
- Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
- Working on the Media Mix Models, Full Funnel Model, Multitouch Attribution etc. to optimize the media
- Devise and utilize algorithms and models to mine data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
- Conduct causality experiments by applying A/B experiments to identify the root issues of an observed result.
- Communicate analytical solutions to stakeholders and implement improvements as needed.
SKILLS & QUALIFICATIONS
- Bachelor’s degree in statistics, applied mathematics, or related discipline.
- Minimum of 4-6 years in a similar role.
- Proficiency with data mining, mathematics, and statistical analysis
- Advanced pattern recognition and predictive modelling experience
- Experience of Media Mix Models, Multitouch Attribution on the working knowledge
- Media understanding is preferrable
- Additional skills of Gen AI, NLP, NLU are optional/ added advantage
- Experience with Excel, Tableau/Looker Studio, SQL, and languages: Python, R
- Storytelling and Data Visualization
- Media understanding is preferrable
- Additional skills of Gen AI, NLP, NLU are optional/ added advantage
- Working knowledge of supervised and unsupervised machine learning techniques such as regression, clustering, classification, decision tree learning, and artificial neural networks
- Comfort working in a dynamic, data-oriented team with several ongoing concurrent projects.
- Professional certifications in data science
PREFERRED QUALIFICATIONS
- Master’s degree in stats, applied math, or related discipline.
- Experience with NoSQL, Pig, Hive, and PySpark, Big Query.