Data Scientist

In this role, the candidate should be highly analytical with a knack for analysis, maths, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyse trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk models, and fraud detection models. Also, integrate the models with the business processes and consuming systems via MLOps processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimisation and using models to evaluate the effectiveness of different courses of action.
Responsibilities:
Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities.
Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modelling inputs to drive decisions.
Work with stakeholders throughout the organisation to identify opportunities for using company data to drive business solutions.
Undertake preprocessing of structured and unstructured data and analyse large amounts of information to discover trends and patterns.
Assess the effectiveness and accuracy of new data sources and data-gathering techniques.
Present information using data visualisation techniques.
Propose solutions and strategies to business challenges.
Coordinate with different functional teams to implement models and monitor outcomes.
Recruit, train, develop and supervise junior-level employees.
Develop processes and tools to monitor and analyse model performance and data accuracy.
Requirements:
Proven experience of 2-6 years as a data scientist.
Postgraduate degree in computer science, engineering, physics, mathematics, econometrics or an MBA with an ML/DS focus.
Knowledge and experience in machine learning, optimisation, statistical, and data mining techniques - regression, simulation, clustering, decision trees, classification algorithms (bagging/boosting), and neural networks.
Knowledge of SQL, Python, and SPARK; familiarity with Scala, Java or C++ is an asset. Candidates with experience of working on the AWS stack will be preferred; however, this is not a compulsory requirement.
Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, and Gurobi would be an added advantage.
Desired Personal Qualities or Behaviour:
Strong analytical critical thinking skills and business acumen.
Strong commitment to professional development.
Process-orientated and excellent time management skills.
Ability to adapt to new situations and issues and to solve problems.
Good organisational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and members and/or customers alike.

Experience
2-6 yrs