Associate Technical Scientist

Assurant, Inc.; United States; Remote; USD 80,000 - 100,000; Full time

Job summary

An innovative company is seeking a Data Scientist to leverage analytical techniques and machine learning tools to solve complex data problems. This role involves developing and maintaining machine learning models, transforming data into actionable insights, and supporting AI product maturity. The ideal candidate will have a strong background in data science, with experience in Python and SQL, and a passion for driving data strategies. Join a dynamic team where your contributions will enhance decision-making and optimize business operations, all while working remotely from the comfort of your home.

Qualifications

• 3+ years of experience in developing ML models and data engineering.
• Proficient in data science tools like Python, SQL, and Hadoop.

Responsibilities

• Develop machine learning solutions for complex business problems.
• Support re-training of existing ML models and ensure compliance.

Skills

Machine Learning

Python

SQL

Data Engineering

Data Analysis

Statistics

Business Intelligence

Data Visualization

Generative AI

Cloud Technologies

Education

Bachelor’s Degree in Statistics

Master’s Degree in a related field

Tools

PySpark

Hadoop

Tableau

Power BI

Advanced Excel

R

Job description

Associate Technical Scientist, GCC, India

The Data Scientist is responsible for using analytical techniques to solve and support complex data science problems. This role will work alongside senior team members to leverage machine learning tools that advance Assurant’s business. The Data Scientist will refresh existing ML models and bring maturity to the data science solutions.

This position will be Remote at our India location. But we are looking for the candidates from Bangalore, Chennai & Hyderabad regions only.

What will be my duties and responsibilities in this job?

Creating Value Through Data (15%)

• Produce clear, insightful, understandable work products (visualizations, reports, presentations, etc.) to outline actionable recommendations.
• Transform data into insights by leveraging internal and external tools (e.g., Python, SQL, Hadoop, Excel, Sawtooth, Power BI, etc.) to identify and quantify opportunities.
• Build studies that add substantial value to the decision-making process through proactive data analysis, reporting, and research.

Model Development (30%)

• Develops machine learning solutions for complex business problems; examine data and develop machine learning solutions for adding business value.
• Devises new algorithmic approaches to solving difficult quantitative problems using large-scale enterprise data sources.
• Develop automated ML models to standardize the refresh process to drive data consistency and quality.

AI Product Maturity, Support & Maintenance (40%)

• Support re-training and enhancement of existing ML models to facilitate growth and maintenance of AI products.
• Proactively identify the opportunities to drive and engage the data science and engineering teams to bring maturity to the AI product implementation methodology.
• Ensures data and model governance is established to comply with internal audit requirements and ensures compliance with data governance and data privacy policies.
• Support ad hoc analytical projects.

Communicating Insights (5%)

• Presents analysis and resulting recommendations to senior team members.
• Leverages data to present compelling business cases to optimize investments and operations.

Support Data Strategies (10%)

• Remains abreast of developments in the field(s) of insurance, management, and data sciences by attending self-development programs, interacting with peers, and reviewing pertinent literature. Incorporates advancements when practicable and cost-effective.
• Participate and drive data modeling and governance best practices.
• Proactively engages internal teams to discover areas of analytical needs.

What are the requirements needed for this position?

• 3 years - Experience in developing ML models, large scale solution implementation, data engineering & management, business analysis, research, statistics, applied mathematics, business intelligence, or related fields.
• 3 years - Experience with data science tools (e.g., Python, PySpark, SQL, Hadoop, Advanced Excel, Tableau, Power BI, Sawtooth, CART, R, etc.) and relational database software
• 2 years - Experience in data analysis that includes translating insights into recommendations.
• 2 years - Experience in an analytical role involving data extraction, analysis, statistical or machine learning modeling, and communication.
• 1 year experience in developing and implementing Generative AI algorithms and applications.
• Bachelor’s Degree in Statistics, Economics, Applied Mathematics, Computer Science, or Information Management; or equivalent is required.
• Writes efficient code that incorporates best practices and standardized methodologies for implementing Data Science solutions.

What other skills/experience would be helpful to have?

• Master’s Degree preferred in business, mathematics, computer science, or a related field.
• Experience in performing statistical analyses, such as predictive modeling, time series analysis, exploratory data analysis, segmentation, cluster analysis, retention, etc.
• Strong written, verbal, and interpersonal communication skills. Ability to effectively communicate at all levels in the organization.
• Experience with data storytelling and distilling complex information into understandable ideas.
• Experience working in the insurance industry.
• Experience with cloud technologies (e.g., Apache Spark, Azure (Databricks, Azure ML, Cognitive Services)).

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