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 a 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 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 to the business.
Identifying new value pockets and bring key business stakeholders on board and enable 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 we need from you?
We need a strong individual contributor with excellent delivery skills. Experience of presenting customer centricity solutions and understanding of the business will also be a key skill for this role.
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 Finance domain using analytics
Understanding of 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
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