Key Responsibilities

<ul>
<li>Develop and deploy fraud detection models for LTC insurance claims using statistical and machine learning techniques</li>
</ul>

<ul>
<li>Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing to identify fraud patterns and anomalies</li>
</ul>

<ul>
<li>Build, evaluate, and optimize traditional statistical models as well as tree-based models such as Random Forest, XGBoost, CatBoost, LightGBM etc.</li>
</ul>

<ul>
<li>Independently conduct data analysis, research, and model experimentation, and translate findings into actionable insights</li>
</ul>

<ul>
<li>Write clean, efficient, and production-ready code using Python and SQL</li>
</ul>

<ul>
<li>Work extensively with large datasets using cloud platforms, primarily Google Cloud Platform (GCP)</li>
</ul>

<ul>
<li>Query and manage data using BigQuery, and handle datasets stored in Cloud Storage (Buckets)</li>
</ul>

<ul>
<li>Use Git for version control, collaboration, and code review</li>
</ul>

<ul>
<li>Prepare clear, concise, and impactful presentations for clients, explaining analytical findings to both technical and non-technical stakeholders</li>
</ul>

<ul>
<li>Collaborate with business, data engineering, and client teams to ensure models align with fraud investigation and business objectives</li>
</ul>

Qualifications

Required Skills &amp; Experience

<ul>
<li>6–7 years of hands-on experience in data science, analytics, or applied machine learning</li>
</ul>

<ul>
<li> Strong understanding of statistical modeling, probability concepts and hypothesis testing</li>
</ul>

<ul>
<li>Proven experience with tree-based and ensemble machine learning models (RF, XGBoost, CatBoost, LightGBM)</li>
</ul>

<ul>
<li>Expert-level SQL for data extraction, transformation, and analysis</li>
</ul>

<ul>
<li>Strong Python skills for data analysis and modeling</li>
</ul>

<ul>
<li>Experience using Git for source code management</li>
</ul>

<ul>
<li>Solid exposure to cloud-based analytics environments, preferably Google Cloud Platform (GCP), BigQuery and Cloud Storage</li>
</ul>

<ul>
<li>Ability to work independently, manage deliverables, and drive tasks end-to-end</li>
</ul>

<ul>
<li>Excellent verbal and written communication skills, essential for a client-facing role Candidate Profile</li>
</ul>

<ul>
<li>Bachelor’s/Master's degree in economics, statistics, mathematics, computer science/engineering, operations research or related analytics areas</li>
</ul>

<ul>
<li>Strong data analysis experience with complex, real-world datasets</li>
</ul>

<ul>
<li>Superior analytical thinking and problem-solving skills</li>
</ul>

<ul>
<li>Outstanding written and verbal communication skills, with confidence in client interactions</li>
</ul>

Data Scientist

India

Key Responsibilities Develop and deploy fraud detection models for LTC insurance claims using statistical and machine learning techniques Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing to identify fraud patterns and anomalies Build, evaluate, and optimize traditional statistical models as well as tree-based models such as Random Forest, XGBoost, CatBoost, LightGBM etc. Independently conduct data analysis, research, and model experimentation, and translate findings into actionable insights Write clean, efficient, and production-ready code using Python and SQL Work extensively with large datasets using cloud platforms, primarily Google Cloud Platform (GCP) Query and manage data using BigQuery, and handle datasets stored in Cloud Storage (Buckets) Use Git for version control, collaboration, and code review Prepare clear, concise, and impactful presentations for clients, explaining analytical findings to both technical and non-technical stakeholders Collaborate with business, data engineering, and client teams to ensure models align with fraud investigation and business objectives Qualifications Required Skills &amp; Experience 6–7 years of hands-on experience in data science, analytics, or applied machine learning Strong understanding of statistical modeling, probability concepts and hypothesis testing Proven experience with tree-based and ensemble machine learning models (RF, XGBoost, CatBoost, LightGBM) Expert-level SQL for data extraction, transformation, and analysis Strong Python skills for data analysis and modeling Experience using Git for source code management Solid exposure to cloud-based analytics environments, preferably Google Cloud Platform (GCP), BigQuery and Cloud Storage Ability to work independently, manage deliverables, and drive tasks end-to-end Excellent verbal and written communication skills, essential for a client-facing role Candidate Profile Bachelor’s/Master's degree in economics, statistics, mathematics, computer science/engineering, operations research or related analytics areas Strong data analysis experience with complex, real-world datasets Superior analytical thinking and problem-solving skills Outstanding written and verbal communication skills, with confidence in client interactions

Data Scientist · New Delhi

Job highlights

Skillset required

Job Description

Job Description for Data Scientist

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