Associate Data Scientist - Python/SQL (2-8 yrs)

Job Description :

We are looking for a Data Scientist to analyse large amounts of raw information to find patterns and to suggest changes in the existing processes for improved customer experience /satisfaction. The person will be responsible to build data products to extract valuable business insights.

In this role, s/he should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. S/he should have a passion for machine-learning and research.

Major Roles & Responsibilities :

- Identify valuable data sources and automate collection processes.

- Undertake to preprocess of 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.

Skills Required :

- Knowledge of banking products and processes.

- Strong understanding of data management practices, data architecture, data quality, and data governance frameworks.

- Proficiency in data analytics tools, data visualization tools, and data integration technologies.

Job Specification :

Qualification : Graduate or Post Graduate degree in Computer science, Data Management, Information Systems, Engineering, Mathematics, Statistics, Economics, Econometrics, or a related field.

Years of Experience : At least 2 years of experience as a data scientist or data analyst, preferably in Bank/ Financial Institution/ BFSI / Fintech.

Experience in :

- Experience in data mining.

- Knowledge of R, SQL and Python; familiarity with Java or Scala is an asset.

- Hands-on experience in working with Dplyr, Lubridate, RMarkdown libraries.

- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

- Experience with data visualization tools, such as D3.js, GGplot, Shiny, etc.

- Good applied statistics skills, such as distributions, statistical testing, regression, etc.

- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop).

- Strong math skills (e.g. statistics, algebra).