If you are a data scientist with a passion to show business impact and value to the business with your data science skills, this could be the right opportunity for you to apply.

What’s the role?

 As a data scientist, you’re going to be responsible for:

• End-to-end delivery of specific analytics projects in the Finance domain.
• Developing advanced Data science solutions for problem statements in Finance.
• Generating business insights from data analytics at the request from the business, generate and enable value for the business.
• Identifying new value pockets and bringing key business stakeholders on board and enabling value through project delivery.
• Setting up and demonstrating world-class standards and best practices in project execution and quality of delivery.
• Articulating clearly, the data science work, its approach, and its value to all stakeholders.

What do we need from you?

We need a strong individual contributor with excellent delivery skills. Experience in presenting customer centricity solutions and understanding of the business will also be a key skill for this role.

Requirements:

• Strong experience in data science/Analytics projects, particularly Forecasting (great if some work is documented in a GitHub repo)
• It would be an advantage if the candidate has completed 1 to 2 projects in the Finance domain using analytics
• Understanding Finance/ Financial Accounting is an additional advantage
• Working knowledge of SQL and Python or R is essential
• Familiarity with key concepts of object-oriented programming
• Knowledge of SAP, Power BI, and/or Alteryx would be an advantage
• Proficiency in any other programming languages (especially C++, Java, SCALA) would be an advantage; knowledge of cloud technology would be an asset
• Expertise in Statistics / Mathematics [Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution/probability theory]
• Expertise in Advanced Timeseries forecasting techniques, Advanced Machine learning techniques [ Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction/engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling), Natural Language Generation