Purpose of Role
- In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data.
- To help our company analyze trends to make better decisions.
- Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, integrate the models with the business processes and consuming systems via ML Ops processes.
- The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action.
Key Accountabilities
Responsibilities will include but will not be restricted to:
- Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities.
- Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
Technical Requirements (what)
- Proven experience of 8+ years as a Data Scientist.
- Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus.
- Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement.
- Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks.
Desired Personal Qualities or Behavior
- Strong Analytical critical thinking skills and business acumen
- Strong commitment to professional development.
- Process Oriented and excellent time management skills.
- Ability to adapt to new situations and issues and to solve problems.
- Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike.
