ROLE AND RESPONSIBILITIES

We are looking for a Data Scientist who will support a variety of AI applications and projects.

The ideal candidate is skilled at using large data sets to find opportunities for process optimization, and using models to test the effectiveness of different courses of action.

The ideal candidate will be expected to:

1. Create new AI & ML use case implementations based on client data and problem statements
2. Have strong experience using a variety of data mining & analysis methods, using a variety of data

tools to build, implement & execute models & simulations

1. Have a proven ability to drive business results with their data-based insights and model outputs
2. Be comfortable working with a wide range of stakeholders and functional teams.
3. Have a passion for discovering solutions hidden in large data sets

The candidate will also preferably have had good exposure and experience to standard software development and testing techniques, working with organisational and enterprise software development teams in the past, whether by developing AI & ML models for inclusion in business software or applying AI & ML techniques to optimise business software delivery & quality processes.

Work with stakeholders throughout the organization to identify opportunities to leverage data to drive business solutions.

Mine and analyse data from client systems to implement use cases

Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms to apply to data sets.

Use predictive modelling to increase and optimize QA and other business outcomes Test

and assure the quality of AI & ML models, their effectiveness and fitness for purpose

Coordinate with different functional teams to implement models and monitor outcomes.

Develop processes and tools to monitor and analyse model performance and data accuracy.

Must Have

0-3 Year’s Experience in Data Science.

Knowledge in implementing learning models and Data Science techniques in either R or Python

Ability to learn new AI/ML tools and languages and use them effectively.

Knowledge in Hadoop is a must.

Knowledge in creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modelling, clustering, decision trees, neural networks, etc.

Demonstrated experience in data retrieval from various SDLC systems and analytic reporting databases. Familiarity with databases and database query languages such as MySQL, Oracle SQL, MS SQL, MongoDB Experience with R, Python, and other programming languages. Knowledge of software engineering and structured software development.

Ability to interface effectively with client and work constructively on a team. Demonstrated ability performing statistical data analysis. Excellent verbal and written communications skills. Desirable Experience

Familiarity with NLP algorithms such as LSA, LDA, and QNLI Familiarity with Deep Learning for Machine Vision

Familiarity with common HDFS tools such as Hadoop Familiarity with cloud computing environments and data science tools such as AWS, SageMaker, GCP and Databricks Benefits