HLE Nepal
Multinational Companies

Who We Are:

Alaya is a place where dreams take shape and grow. Originally founded as Home Loan Experts in 2007, the company expanded its reach by establishing HLE Nepal in 2012, which later rebranded to Alaya. This transformation signifies Alaya's unwavering commitment to supporting not only its customers and clients but also its community and colleagues. Alaya goes beyond being a mortgage industry leader, offering a boundless place of limitless potential where individuals can dedicate their hearts, flourish, and shine. Alaya redefines the power of place, becoming “Your Place” to dedicate your heart, to flourish, and to shine.
Alaya and Home Loan Experts offer more than mortgage expertise; it's a place where you can thrive. Here, we value Passion, Care, and Oneness—caring deeply for our team and embracing unity. Together, the Alaya team works as one family, united in their mission to help people realise their dreams.

To know more about us and careers, please visit Alaya and to know more about our mortgage business, please visit Home Loan Experts.

Who We Are:

Data Manager

Views: 2212 | This job is expired 3 years, 11 months ago

Basic Job Information

Job Category	:	IT & Telecommunication
Job Level	:	Mid Level
No. of Vacancy/s	:	[ 1 ]
Employment Type	:	Full Time
Job Location	:	Jawalakhel, Lalitpur, Nepal
Offered Salary	:	Negotiable
Apply Before(Deadline)	:	Aug. 10, 2021 23:55 (3 years, 11 months ago)

Job Specification

Education Level	:	Under Graduate (Bachelor)
Experience Required	:	More than or equal to 5 years
Professional Skill Required	:	Communication Time Management Presentation Teamwork Interpersonal Skills

Other Specification

Qualification and Experience:

BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred.
5+ years as Data Analyst/ Data Scientist.

Skills:

Extensive background in data mining and statistical analysis.
Extensive experience in Data Engineering and Data Lakes on AWS.
Knowledge of customer journey models and customer segmentation.
Extensive experience with Tableau.
Extensive experience with Amazon warehouse data suite.
Experience with analysis problem-solving and interpreting financial, customer, third party data.
Advanced data/insights interpretation skills.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Experience in stakeholder analysis.
Excellent communication skills, both written and verbal.
Superior public presentation skills.
Understanding of networks, databases and other technology.
Advanced Excel skills.
Able to work with minimum supervision.
Ability to work under pressure.
Driven and a strong desire to learn and a Team player.

Desired Experience:

Coding knowledge and experience with several languages: C, C++, Java.
Advanced experience on R, Python, SQL, Google analytics and Tableau.
Project management.

Job Description

Primary duties:

Work with HLE business leaders (Senior Digital Marketing Manager, Digital Marketing Manager, CEO, Founder, GM Broking, Tech Team Manager) to understand the business needs for data and translate them into decision-ready user metrics.
Map and optimize the customer journey data flow.
Identify valuable data sources and automate collection processes.
Deliver and implement a data strategy, (including managing/ prioritizing data and business intelligence requests) and converting them into clearly defined projects with well-defined parameters and deliverables.
Build and implement a data lake to enable one central source of data truth.
Hydrate the HLE AWS data lake using best practice solutions.
Working within the data lake with Glue.
Transforming Data with Glue.
Consuming the data lake - reporting, analytics, Machine Learning.
Bridging Data for AI?ML using Amazon Sagemaker.
Analyze large amounts of information to discover trends and patterns.
Undertake preprocessing of structured and unstructured data.
Develop custom data models and algorithms to apply to data sets.
Build customer propensity models and machine learning algorithms.
Use predictive modelling to increase and optimize customer experiences, revenue generation, marketing targeting and other business outcomes.
Build and implement advanced machine learning algorithms.
Implement regression models, simulations, scenario analysis, clustering, decision trees, neural networks, etc.to design the optimal data architecture for HLE.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Research, acquire and apply mortgage industry knowledge to influence product design decisions.

Secondary duties:

Document business processes and propose innovative improvements.
Develop a clear definition and acceptance criteria for each of the features to ensure the business requirements will be addressed.
Ensure team activities are aligned with project objectives and stakeholders expectations.
Provide regular updates to key stakeholders.
Any other relevant duties as required from time to time.

The Benefits of Joining us!

SSF in addition to the monthly salary.
Get to work with one of our top outsourcing partners.
A secure long-term role.
Paid annual leave and sick leave.
Paid maternal and parental leaves.
A 5-day work week except for 1 Sunday of the month.
An environment that values continuous learning and development.
Office-sponsored daily breakfasts and other benefits.
Recreation room to unwind and chill!
Parties and events – we want you to have some fun at work!
Accident and health insurance for you and your two family members.
Office sponsored 'Employee Assistance Program'.

Work hours: 8:00 am to 4:00 pm including a 1-hour lunch break (non-negotiable)

Note: Position description will be discussed in detail during the virtual interview. Only short-listed candidates will be contacted.

This job has expired.

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