Data Scientist with impressive exposure to data. Interested in consumer analytics, business strategy and design thinking inclined by data science. Also have understanding customers’ behaviours, behavioural segmentation, time series analysis, predictive modelling, hypotheses testing and data mining for advisory purposes in strategy formulation, optimization and solving of complex business issues. Analyze a large amount of raw information to find patterns that will help improve company products.
Responsibilities:
•Selecting features, building and optimizing classifiers using machine learning techniques
•Undertaking data collection, preprocessing and analysis
• Presenting information using data visualization techniques
•Identify valuable data sources and automate collection processes
•Undertake to preprocess structured and unstructured data
•Analyze large amounts of information to discover trends and patterns
•Build predictive models and machine-learning algorithms
•Combine models through ensemble modelling
•Present information using data visualization techniques
•Propose solutions and strategies to business challenges
•Collaborate with engineering and product development teams
•Analyze raw data from zendesk and create datasets accordingly
•Data mining using state-of-the-art methods
•Enhancing data collection procedures to include information for building analytic systems
•Processing, cleansing, and verifying the integrity of data used for analysis
•Doing ad-hoc analysis and presenting results in a clear manner
•Creating automated anomaly detection systems and constant tracking of its performance
Requirements:
•Minimum 3 years of experience in artificial intelligence and machine learning with proven experience as a Data Scientist and Data Analyst
•Experience in handling the planning and development of design, procedures and developing data insights and data mining techniques.
•Experience in designing and implementation of data models, performing the statistical analysis, and created predictive models. Expertise in machine-learning and research.
•Understanding of machine-learning and operations research
•Knowledge of R, SQL and Python; familiarity with Scala, Java or C is an asset
•Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
•Analytical mind and business acumen
•Strong math skills (e.g. statistics, algebra)
•Problem-solving aptitude
•Excellent communication and presentation skills
•BS in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
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