Data Scientist

Role purpose 

As a Data Scientist at Prevalent, you'll help turn complex data into clear, actionable insights that solve real 
business problems and support smarter decisions. Using advanced analytics, machine learning, and 
statistical methods, you'll build predictive models and data-driven solutions that enhance our key products—
Exposure Management and Data Fabric.
You'll work with data from various sources, uncover patterns, and deliver insights that improve how 
organizations manage risk and large-scale data. This role is a great opportunity to apply your data science 
skills to innovative, AI-powered products and make a direct impact on product development and business 
success.

Key accountabilities

• Understanding business requirements through collaboration with SMEs and translating them into data 
science solutions
• Performing data assembly, cleansing, validation, and visualization
• Applying statistical modelling, supervised and unsupervised machine learning, and mathematical 
programming
• Inspecting data for consistency and modifying designs as needed
• Communicating predictions and findings through visualizations and reports
• Creating prototypes for data manipulations, visualizations, and modelling
• Validating designs with SMEs and iterating based on feedback
• Ensuring software implementation matches design expectations through testing
• Keeping up with industry trends and following a personal education plan for technology and solution 
architecture

Skills and Experience

• Relevant experience working in Data Science
• Experience in working with Big Data and common data science tools such as R, Python, Spark etc 
• Self-motivated individual capable of working in a fast-paced environment
• Great verbal and written communication skills
• A strong analytical mind-set
• Good understanding and expertise in processing large datasets 
• Good working knowledge in implementation of various ML algorithms in big data environment, 
advanced ML concepts like ANN, Deep learning etc 
• Understanding of data visualization tools, such as D3.js, Tableau, etc
• Familiarity with Scala, HIVE is desired 
• Good scripting and programming skills; SQL proficiency 
• Understanding of and proficiency in NLP 
• Understanding of a range of statistical and machine learning techniques and algorithms, such as logistic regression, KNN, decision trees, SVM, CNN, etc 
• Good understanding of the process workflow:
      o Problem definition to hypothesis building 
      o Prototype model building using python/R  
      o Implementation of ML problems in big data.
      o Performance Monitoring & Evaluation of System