All the candidates / student are inform that the ANZ is officially hire the candidates for the position Data Scientist and those candidates who are pursuing / completed there BE/ B.Tech/ME/M.Tech are eligible for this post interested candidates are fill out online application throw our given link below.
ANZ offers financial services was founded in 1835 and it’s headquarters are located in Melbourne, Australia. The CEO of the company since 2016 is Shayne Elliott. The company’s subsidiary is ANZ Bank New Zealand. A total of 39,196 people were employed by the company as of the reports produced in 2021.
| Company | ANZ |
| Position | Data Scientist |
| Location | Bengaluru |
| Experience | Freshers |
| Qualification | BE/ B.Tech/ME/M.Tech |
| Batch | 2018/19/20/21/22/23 |
| Salary | Up to 12 LPA (Expected) |
Jobrole & Responsibilities :
Address and solve complex business issues using large amounts of data
Develop advanced algorithms that transform key business processes and automate banker decisions and activities
Implement a fact-based culture throughout the bank.
Continuous generation, monitoring, presenting and conducting of ‘fact-based’ analysis and models to use at any time for the development and improvement of relevant and innovative propositions
Design, build, deploy, monitor and assess relevant models for customers, clients, products and channels
Develop tools and methods to scientifically profile customers and customer segments, products and channels and associated costs, revenues, risks and opportunities
Source data from a variety of sources to combine, synthesise and analyse to support campaigns, pricing, propositions and other decisions
Initiate, design and implement innovative capabilities in the field of data science
Lead, optimise, design and execute business interventions (customers and operational) to uplift customer engagement and business performance
Skills :
Solid understanding of predictive modelling, pattern recognition, clustering, supervised and unsupervised learning
Experience in Python and key supporting packages/libraries for Data Science
Experience managing Machine learning lifecycle using MLFlow and performing data processing & transformation using PySpark and Object Store
Experience building and deploying pipelines for Model training, deployment and monitoring using Airflow and integrating data quality checks.
Experience setting up dashboards for ongoing monitoring of ML Models.
Strong ability to translate data insights into practical business recommendations
Strong statistical modelling and data management skills
Strong communication and presentation skills
Ability to lead and inspire a team
Good understanding of the Banking system and products, service, channels
Strong customer lens and affinity
Analytical and inquisitive mindset to continuously improve the level of decisions automated
Ability to effectively communicate to all stakeholders (technical and non-technical)
Apply process for this position
These are the followings steps for filling the application form:-
- As always, read all the information on this page and check the qualifications.
- After reviewing and reading, scroll down and click on Apply Now text.
- You will be redirected to the job page on Superset’s website.
- Recheck all the details and information provided there.
- Click on the Apply now button.
- If you already have an account on the Superset website, then log in. Otherwise, create a new one.
- After signing in, enter all the required details and apply.
Eligible and Interested candidates fill out the online application form through our link below.