Info Resume Edge
We are hiring on behalf of one of our clients, a leading
RegTech SaaS company
that helps global enterprises in fintech, banking, and compliance sectors manage risk and regulatory requirements. The company leverages AI and data-driven insights to power its solutions, and now seeks
Lead
Data Scientists
to strengthen its product innovation and analytics capabilities. Role Overview
As a
Data Scientist , you will play a critical role in designing, developing, and deploying machine learning and statistical models to solve complex business and compliance challenges. You will collaborate with engineering, product, and compliance experts to build scalable data-driven solutions that improve product accuracy, efficiency, and customer outcomes. Key Responsibilities
Collect, clean, and analyze large structured and unstructured datasets from multiple sources. Develop and implement
machine learning models
for fraud detection, risk scoring, identity verification, and compliance monitoring. Conduct
statistical analysis, feature engineering, and predictive modeling
to extract insights and improve product performance. Collaborate with engineering teams to
deploy models into production
at scale. Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness. Research and implement
state-of-the-art algorithms
in AI/ML relevant to RegTech (e.g., anomaly detection, NLP, computer vision). Monitor, evaluate, and continuously improve models for performance, fairness, and compliance. Prepare clear documentation, dashboards, and reports to communicate findings to both technical and non-technical stakeholders. Requirements
Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. 25 years of experience as a
Data Scientist or ML Engineer
(preferably in SaaS, fintech, or RegTech). Proficiency in
Python, R, or Scala , with strong knowledge of libraries such as scikit-learn, TensorFlow, PyTorch, or similar. Strong understanding of
statistics, probability, and machine learning techniques
(classification, clustering, NLP, anomaly detection). Experience working with
SQL and NoSQL databases . Knowledge of
big data tools
(Spark, Hadoop, or similar) is a plus. Experience deploying ML models to production environments (AWS, GCP, or Azure). Strong analytical, problem-solving, and communication skills. Preferred Skills
Hands-on experience with
computer vision techniques
(e.g., object detection, OCR, facial recognition, document image analysis). Expertise in
deep learning frameworks
(TensorFlow, PyTorch, Keras) applied to image-based models. Familiarity with
image preprocessing techniques
(augmentation, noise reduction, image normalization). Understanding of
explainable AI in computer vision
for compliance-driven use cases. Ability to translate complex image-based model outputs into
product-ready solutions .
#J-18808-Ljbffr
RegTech SaaS company
that helps global enterprises in fintech, banking, and compliance sectors manage risk and regulatory requirements. The company leverages AI and data-driven insights to power its solutions, and now seeks
Lead
Data Scientists
to strengthen its product innovation and analytics capabilities. Role Overview
As a
Data Scientist , you will play a critical role in designing, developing, and deploying machine learning and statistical models to solve complex business and compliance challenges. You will collaborate with engineering, product, and compliance experts to build scalable data-driven solutions that improve product accuracy, efficiency, and customer outcomes. Key Responsibilities
Collect, clean, and analyze large structured and unstructured datasets from multiple sources. Develop and implement
machine learning models
for fraud detection, risk scoring, identity verification, and compliance monitoring. Conduct
statistical analysis, feature engineering, and predictive modeling
to extract insights and improve product performance. Collaborate with engineering teams to
deploy models into production
at scale. Partner with product teams to design experiments (A/B testing) and evaluate feature effectiveness. Research and implement
state-of-the-art algorithms
in AI/ML relevant to RegTech (e.g., anomaly detection, NLP, computer vision). Monitor, evaluate, and continuously improve models for performance, fairness, and compliance. Prepare clear documentation, dashboards, and reports to communicate findings to both technical and non-technical stakeholders. Requirements
Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field. 25 years of experience as a
Data Scientist or ML Engineer
(preferably in SaaS, fintech, or RegTech). Proficiency in
Python, R, or Scala , with strong knowledge of libraries such as scikit-learn, TensorFlow, PyTorch, or similar. Strong understanding of
statistics, probability, and machine learning techniques
(classification, clustering, NLP, anomaly detection). Experience working with
SQL and NoSQL databases . Knowledge of
big data tools
(Spark, Hadoop, or similar) is a plus. Experience deploying ML models to production environments (AWS, GCP, or Azure). Strong analytical, problem-solving, and communication skills. Preferred Skills
Hands-on experience with
computer vision techniques
(e.g., object detection, OCR, facial recognition, document image analysis). Expertise in
deep learning frameworks
(TensorFlow, PyTorch, Keras) applied to image-based models. Familiarity with
image preprocessing techniques
(augmentation, noise reduction, image normalization). Understanding of
explainable AI in computer vision
for compliance-driven use cases. Ability to translate complex image-based model outputs into
product-ready solutions .
#J-18808-Ljbffr