Hiroshi Kaneko - Senior Data Scientist

Q: Where is Hiroshi based?

Hiroshi is based in Warsaw, Poland .

Q: What languages does Hiroshi speak?

Hiroshi speaks the following languages: Japanese (Native), English (Advanced), Polish (Intermediate), German (Elementary) .

Q: How many years of experience does Hiroshi have?

Hiroshi has at least 11 years of experience. During this time, Hiroshi has worked in at least 3 different roles and for 3 different companies . The average length of individual experience is 4 years and 9 months . Note that Hiroshi may not have shared all experience and actually has more experience.

Q: What is Hiroshi's latest experience?

Hiroshi's most recent position is Senior Data Scientist at Siemens Group .

Q: What companies has Hiroshi worked for in recent years?

In recent years, Hiroshi has worked for Siemens Group , EPAM Systems , and Fujitsu .

Q: Which industries is Hiroshi most experienced in?

Hiroshi is most experienced in industries like Information Technology (IT) , Manufacturing , and Retail . Hiroshi also has some experience in Banking and Finance .

Q: Which business areas is Hiroshi most experienced in?

Hiroshi is most experienced in business areas like Information Technology (IT) , Business Intelligence , and Product Development . Hiroshi also has some experience in Quality Assurance (QA) , Operations , and Supply Chain Management .

Q: Which industries has Hiroshi worked in recently?

Hiroshi has recently worked in industries like Information Technology (IT) , Manufacturing , and Retail .

Q: Which business areas has Hiroshi worked in recently?

Hiroshi has recently worked in business areas like Information Technology (IT) , Business Intelligence , and Product Development .

Recommended expert

Warsaw, Poland

Experience

Oct 2024 - Sep 2025

1 year

Munich, Germany

Senior Data Scientist

Siemens Group

Resolved IoT sensor data schema evolution in Azure ML by implementing data contracts with automatic backfills from manufacturing equipment logs, reducing pipeline failures by 65%.
Addressed forecast accuracy degradation for spare parts demand by implementing Feast feature store with SCD type 2 handling from SAP ERP data, improving MAE by 23% for time series models.
Eliminated production model staleness by establishing automated Azure ML Pipelines with drift detection on feature distributions, enabling 95% automated retraining cadence.
Secured model endpoints by implementing RBAC and approval workflows in MLflow Model Registry with PII masking for customer service data, achieving compliance audit pass.

Jun 2021 - Aug 2024

3 years 3 months

Warsaw, Poland

Data Scientist

EPAM Systems

Solved transaction latency spikes in real-time fraud detection by optimizing XGBoost classification with feature selection from payment gateway APIs, reducing inference time from 120ms to 45ms while maintaining 0.95 AUC.
Addressed feature consistency across training-serving by implementing Feast feature store with Spark processing from Kafka streams and merchant DBs, eliminating 80% of training-serving skew incidents.
Reduced false positive alerts by 60% through Evidently monitoring dashboard with custom metrics for data drift and prediction distribution shifts on transaction data.
Accelerated model iteration cycle by establishing MLflow experiment tracking with automated lineage from feature definitions to model versions, cutting experiment setup time by 70%.
Eliminated manual deployment errors by implementing GitHub Actions CI/CD with integration tests for data schemas and model performance thresholds on credit scoring models.
Resolved cost overruns in model serving by implementing autoscaling policies and resource quotas for online endpoints, reducing inference costs by 35% while maintaining 99.9% uptime SLA.

Apr 2014 - May 2021

7 years 2 months

Japan

MLOps from Junior ML Engineer

Fujitsu

Solved batch prediction bottlenecks for customer churn by containerizing Scikit-learn models with Airflow orchestration from CRM data, reducing processing time from 8 hours to 45 minutes.
Addressed model reproducibility issues by pioneering MLflow tracking for experiment metadata and hyperparameters across retail forecasting projects, enabling 100% experiment replication.
Eliminated training-serving skew in recommendation systems by implementing feature versioning with validation checks against user behavior logs, improving offline-online consistency by 40%.
Resolved production incident response delays by establishing basic monitoring with custom metrics for model accuracy and data quality on manufacturing sensor data, reducing mean time to detection by 65%.
Accelerated model deployment from weeks to days by introducing Docker-based serving patterns with blue-green deployment for A/B testing of pricing optimization models.

Industries Experience

See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.

Experienced in Information Technology (10.5 years), Manufacturing (8 years), Retail (7 years), and Banking and Finance (3 years).

Information Technology

Manufacturing

Retail

Banking and Finance

Business Areas Experience

The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.

Experienced in Information Technology (11.5 years), Business Intelligence (7 years), Product Development (3 years), Quality Assurance (3 years), Operations (1 year), and Supply Chain Management (1 year).

Information Technology

Business Intelligence

Product Development

Quality Assurance

Operations

Supply Chain Management

Summary

10+ years of experience building production ML systems across manufacturing and financial services domains. Expert in end-to-end MLOps implementation with Azure ML for automated pipelines, feature stores, and model serving. Proven track record in establishing robust monitoring frameworks for data quality and model performance. Specialized in designing scalable experimentation platforms that accelerate model development while ensuring governance and reproducibility across enterprise environments.

Skills

Cloud/platform: Azure Ml, Databricks, Kubernetes, Docker
Modeling: Xgboost, Lightgbm, Scikit-learn, Tensorflow, Forecasting
Data & Features: Spark, Feast, Delta Lake, Data Contracts
Pipelines/serving: Azure Ml Pipelines, Mlflow, Online Endpoints, Feature Store
Monitoring & Observability: Evidently, Prometheus, Grafana, Data Drift
Devops/sec: Github Actions, Terraform, Rbac, Pii Masking
Experimentation: Mlflow Tracking, A/b Testing, Hypothesis Testing

Languages

Japanese

Native

English

Advanced

Polish

Intermediate

German

Elementary

Education

Apr 2014 - Mar 2016

Tokyo University of Science

Master Of Computer Applications · Computer Applications Development · Japan

Apr 2010 - Mar 2014

Tokyo University of Science

Bachelor Of Science · Computer Science · Japan

Certifications & licenses

AI Skills

Engineering Excellence

exPractice

Fujitsu Learning eXperience

Profile

Created

November 2025

Last Update

November 2025

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Frequently asked questions

Do you have questions? Here you can find further information.

Where is Hiroshi based?

Hiroshi is based in Warsaw, Poland.

What languages does Hiroshi speak?

Hiroshi speaks the following languages: Japanese (Native), English (Advanced), Polish (Intermediate), German (Elementary).

How many years of experience does Hiroshi have?

Hiroshi has at least 11 years of experience. During this time, Hiroshi has worked in at least 3 different roles and for 3 different companies. The average length of individual experience is 4 years and 9 months. Note that Hiroshi may not have shared all experience and actually has more experience.

What roles would Hiroshi be best suited for?

Based on recent experience, Hiroshi would be well-suited for roles such as: Senior Data Scientist, Data Scientist, MLOps from Junior ML Engineer.

What is Hiroshi's latest experience?

Hiroshi's most recent position is Senior Data Scientist at Siemens Group.

What companies has Hiroshi worked for in recent years?

In recent years, Hiroshi has worked for Siemens Group, EPAM Systems, and Fujitsu.

Which industries is Hiroshi most experienced in?

Hiroshi is most experienced in industries like Information Technology (IT), Manufacturing, and Retail. Hiroshi also has some experience in Banking and Finance.

Which business areas is Hiroshi most experienced in?

Hiroshi is most experienced in business areas like Information Technology (IT), Business Intelligence, and Product Development. Hiroshi also has some experience in Quality Assurance (QA), Operations, and Supply Chain Management.

Which industries has Hiroshi worked in recently?

Hiroshi has recently worked in industries like Information Technology (IT), Manufacturing, and Retail.

Which business areas has Hiroshi worked in recently?

Hiroshi has recently worked in business areas like Information Technology (IT), Business Intelligence, and Product Development.

What is Hiroshi's education?

Hiroshi holds a Master in Computer Applications Development from Tokyo University of Science and a Bachelor in Computer Science from Tokyo University of Science.

Does Hiroshi have any certificates?

Hiroshi has 2 certificates. These include: AI Skills and exPractice.

What is the availability of Hiroshi?

Hiroshi is immediately available full-time for suitable projects.

What is the rate of Hiroshi?

Hiroshi's rate depends on the specific project requirements. Please use the Meet button on the profile to schedule a meeting and discuss the details.