Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Role:

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.

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 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