Nurul Amin

Product Manager

Tokyo, Japan18 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led data-driven strategies for C-suite executives.
Expert in PetaByte-scale data management.
Innovative in developing data monetization pathways.

Stackforce AI infers this person is a Data Science and AIML expert in Telecommunications.

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Skills

Core Skills

Data ScienceAimlMachine Learning

Other Skills

3GPPAlgorithmsAnalytical SkillsAnalyticsApplied Machine LearningBusiness AnalysisCCloud ComputingComputer ScienceComputer VisionConsultingDNSData AnalysisData StructuresData Visualization

About

At the helm of Rakuten Mobile’s Network Insights department, my leadership in Data Science and AIML has been instrumental in managing and processing vast datasets and presenting pivotal insights to the C-suite. My tenure has focused on harnessing PetaByte-scale data from diverse sources, driving data-driven strategic decisions that resonate across the entire organization. Collaboration with other business units has been a cornerstone of my role, leveraging my expertise in AIML to identify and convert growth opportunities into tangible data models. This synergy has not only bolstered Rakuten's business intelligence but also paved the way for innovative data monetization pathways, underpinning the organization's expansive vision in a rapidly evolving digital landscape.

Experience

Rakuten mobile, inc.

2 roles

Senior Manager | Network Insights (Data & AI)

Promoted

Jul 2023 – Present · 2 yrs 8 mos

Leading Data, AIML and Analytics activities at Rakuten Mobile.
Managing and processing Peta Byte scale of Data from multiple data sources.
Presenting insights/recommendations in daily executive huddle to the
CEO/CTO/CMO to take data-driven business/strategic decisions.
Analyzing and correlating Customer mobile data, Internet usage data, e-commerce
data, Geo-location data, and Deep Packet Inspection data to generate insights.
Collaborate with other Business Units in entire Group Companies
identify business growth use cases and convert them into tangible data models.
Identify data monetization opportunities and conduct PoC until production.
Architecting big data processing, ETL, Data Pipelines with Python, Apache Spark.
DevOps for in-house Data Lake, S3 Object Storage and Data Warehouse solution.
Handling Data Bus, Streaming (Kafka), Query Engine and Cloud-native DB.
Handling in-house big data SaaS paralleling AWS services.
Data Governance for master data management, data discovery and data security.
Productionize ML application and deploy on Kubernetes cluster.
Handle AI platform for ML Model building, training and validation.
Converts business problems into ML models using Classification, Regression, NLP,
RNN, Clustering, XGBoost, Time-Series etc. Some of the models we developed:
Customer Churn Prediction, Customer Segmentation, CLV/LTV.
Customer Sentiment Analysis from social media posts.
Network Anomaly Detection and Predictive Maintenance model.
Autonomous and self-optimizing systems development.
Build ML pipelines, Feature Engineering and Hyper parameter tuning jobs.
Mentor engineers on deep dive, building insights and executive presentations.
Ensure a learning culture for innovations, new ideas along with the latest tech.