Job VC
Middle Data Scientist
Technologies
Description
Dataforest is looking for a Data Scientist to join an interesting software development project in the field of Cybersecurity. Our client's platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.
Required Qualifications
2+ years
of experience working with large-scale, complex datasets.
Experience with imbalanced data.
High proficiency in Python for data analysis, feature engineering and modeling.
Expertise in exploratory data analysis and preparing clean, structured datasets for model development.
Hands-on experience with AI/ML techniques
:
Supervised (eg. gradient boosting, decision trees, etc.)
Unsupervised (eg. anomaly detection, clustering, etc.)
Familiarity with basic statistical concepts and model evaluation metrics (eg. precision, recall, ROC-AUC).
Upper-intermediate (B2) or higher level of English.
Nice to Have
Hands-on experience in the fraud/risk domain.
Experience with
Databricks (including Pyspark)
for data processing, experimentation, and model development.
Experience in
MLflow
library for experiment tracking and model lifecycle management.
Experience working with diverse data sources (e.g., behavioral, device, or transactional data) and deriving meaningful features.
Experience assessing data quality and validating new data sources in production environments.
Key Responsibilities
Analyze
large-scale transaction datasets to identify fraud patterns and risk signals.
Develop and validate ML models
for risk scoring and fraud detection/classification.
Support deployment
of models into production environments by collaborating with the development team.
Monitor model performance
, conduct regular evaluations, analyze the results.
Perform feature engineering
to continuously improve model performance.
Collaborate
with the client on R&D efforts, including exploratory data analysis, feature development, and testing new approaches.
We offer
Great networking opportunities with international clients, challenging tasks;
Building interesting projects from scratch using new technologies;
Personal and professional development opportunities;
Competitive salary fixed in USD;
Paid vacation and sick leaves;
Flexible work schedule;
Friendly working environment with minimal hierarchy;
Team building activities and corporate events.
Required Qualifications
2+ years
of experience working with large-scale, complex datasets.
Experience with imbalanced data.
High proficiency in Python for data analysis, feature engineering and modeling.
Expertise in exploratory data analysis and preparing clean, structured datasets for model development.
Hands-on experience with AI/ML techniques
:
Supervised (eg. gradient boosting, decision trees, etc.)
Unsupervised (eg. anomaly detection, clustering, etc.)
Familiarity with basic statistical concepts and model evaluation metrics (eg. precision, recall, ROC-AUC).
Upper-intermediate (B2) or higher level of English.
Nice to Have
Hands-on experience in the fraud/risk domain.
Experience with
Databricks (including Pyspark)
for data processing, experimentation, and model development.
Experience in
MLflow
library for experiment tracking and model lifecycle management.
Experience working with diverse data sources (e.g., behavioral, device, or transactional data) and deriving meaningful features.
Experience assessing data quality and validating new data sources in production environments.
Key Responsibilities
Analyze
large-scale transaction datasets to identify fraud patterns and risk signals.
Develop and validate ML models
for risk scoring and fraud detection/classification.
Support deployment
of models into production environments by collaborating with the development team.
Monitor model performance
, conduct regular evaluations, analyze the results.
Perform feature engineering
to continuously improve model performance.
Collaborate
with the client on R&D efforts, including exploratory data analysis, feature development, and testing new approaches.
We offer
Great networking opportunities with international clients, challenging tasks;
Building interesting projects from scratch using new technologies;
Personal and professional development opportunities;
Competitive salary fixed in USD;
Paid vacation and sick leaves;
Flexible work schedule;
Friendly working environment with minimal hierarchy;
Team building activities and corporate events.