Data Scientist

We are seeking a highly skilled

Data Scientist

with experience of 3-5 years

to join our team and lead the development of advanced models that analyze user interaction patterns and measure behavioral dynamics over time. The ideal candidate will have experience working with large-scale interaction data, behavioral analytics, and machine learning for pattern recognition and anomaly detection.

This role will focus on designing, developing, and deploying ML models that leverage

user interaction data

(typing speed, mouse movements, touch patterns, autofill behavior, and behavioral changes over time) to generate meaningful insights and risk scores for understanding user authenticity and identifying behavioral anomalies.

Responsibilities

• Act as a thought partner in defining data science strategy and translating it into practical execution roadmaps.
• Drive experimentation, validation and optimization cycles that balance innovation with real-world reliability.
• Design robust data representations that capture temporal, interaction, and anomaly-based patterns.
• Implement scalable machine learning pipelines for real-time analysis and scoring of user sessions.
• Collaborate with engineering teams to integrate models into production environments.
• Conduct research and stay updated on state-of-the-art approaches in fraud detection, anomaly detection, and behavioral biometrics.

Qualifications

Must-Have:

• Strong background in

Machine Learning, Deep Learning, and Statistical Modeling

.

• Proficiency in

Python

and ML libraries (TensorFlow, PyTorch, Scikit-learn, XGBoost).

• Hands-on experience with

time-series data, anomaly detection, or fraud detection

.

• Strong feature engineering skills, especially with high-dimensional and noisy behavioral data.
• Knowledge of

data processing frameworks

(Spark, Kafka, Flink, etc.) for streaming/real-time data.

• Experience deploying models into

production systems

(ML Ops, APIs, containerized environments).

-

Nice-to-Have:

• Familiarity with

behavioral biometrics, keystroke dynamics, or session replay analysis

.

• Knowledge of

bot detection systems, fraud prevention or cybersecurity applications

.

• Experience with

big data platforms

(Snowflake, Databricks, Hadoop).

Research background in

graph-based ML

,

similarity search

, or

embedding techniques

.