OIP Insurtech
https://www.oipteam.com/career/About
OIP Insurtech streamlines insurance operations and optimizes workflows by combining deep industry knowledge with advanced technology. Established in 2012, OIP InsurTech partners with carriers, MGAs, program managers, and TPAs in the US, Canada, and Europe, especially the UK.
With 1,200 professionals serving over 100 clients, we deliver insurance process automation, custom software development, high-quality underwriting services, and skilled tech staff to augment our clients.
While saving time and money is the immediate win, the real game-changer is giving our clients the freedom to grow their books, run their businesses, and focus on what they love. We’re proud to support them on this journey and make a positive impact on the industry.
Tech stack
Python
Data Science
Machine Learning (ML)Candid answers by the company
Our robotics team has all graduated from our insurance boot camp. They code insurance for a living and bring with them best practices from more than 80 different systems across the insurance ecosystem.
They’ve seen what works for E&S businesses – they’ve built them. And they know what it takes to help your team deliver the better result.
Company social profiles
Jobs at OIP Insurtech
Machine Learning (ML)PythonLocation: Hyderabad, Hybrid
We seek an experienced Lead Data Scientist to support our growing team of talented engineers in the Insurtech space. As a proven leader, you will guide, mentor, and drive the team to build, deploy, and scale machine learning models that deliver impactful business solutions. This role is crucial for ensuring the team provides real-world, scalable results. In this position, you will play a key role, not only by developing models but also by leading cross-functional teams, structuring and understanding data, and providing actionable insights to the business.
What We’re Looking For
● Proven experience as a Lead Machine Learning Engineer, Data Scientist, or a similar role, with extensive leadership experience managing and mentoring engineering teams.
● Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
● Demonstrated success in leading teams that have designed, deployed, and scaled machine learning models in production environments, delivering tangible business results.
● Expertise in machine learning algorithms, deep learning, and data mining techniques, ideally in an enterprise setting.
● Hands-on experience with natural language processing (NLP) and data extraction tools.
● Proficiency in Python (or other programming languages), and with libraries such as Scikit-learn, TensorFlow, PyTorch, etc.
● Strong experience with MLOps processes, including model development, deployment, and monitoring at scale.
● Strong leadership and analytical skills, capable of structuring and interpreting data to provide meaningful business insights and guide decisions.
● A practical understanding of aligning machine learning initiatives with business objectives.
● Industry experience in insurance is a plus but not required.
What You’ll Be Doing
● Lead and mentor a team of strong Machine Learning Engineers, synthesizing their skills and ideas into scalable, impactful solutions.
● Have a proven track record in successfully leading teams in the development, deployment, and scaling of machine learning models to solve real-world business problems.
● Provide leadership in structuring, analyzing, and interpreting data, delivering insights to the business side to support informed decision-making.
● Oversee the full lifecycle of machine learning models – from development and training to deployment and monitoring in production environments.
● Collaborate closely with cross-functional teams to align AI efforts with business goals
and ensure measurable impacts.
● Leverage deep expertise in machine learning, data science, or related fields to enhance document interpretation tasks such as text extraction, classification, and semantic analysis.
● Utilize natural language processing (NLP) to improve our AI-based Intelligent Document Processing platform.
● Implement MLOps best practices, ensuring smooth deployment, monitoring, and maintenance of models in production.
● Continuously explore and experiment with new technologies and techniques to push the boundaries of AI solutions within the organization.
● Lead by example, fostering a culture of innovation and collaboration within the team while effectively communicating technical insights to both technical and non-technical stakeholders.
Candidates not located in Hyderabad will not be taken into consideration.
PythonWe are looking for a forward-thinking AI Engineer who thrives on pioneering advancements in AI technology and its practical applications within the insurance sector. This role is ideal for someone deeply engaged with AI research, enjoys exploring new technologies, and is adept at rapidly transitioning innovative concepts into real-world applications. Join our team to lead the integration of next-gen AI solutions that streamline and transform insurance processes.
Who You Are
An ideal candidate is someone deeply embedded in the AI research community, comfortable navigating uncharted tech territories, and skilled in translating complex theoretical ideas into testable and demonstrable prototypes. You are driven by curiosity and the challenge of solving complex problems that might one day reshape the insurance industry.
What We’re Looking For
● Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. A PhD in AI or a related discipline is highly desirable.
● Experience:
○ Proven experience in AI research and implementation, with a deep
understanding of both theoretical and practical aspects of AI.
○ Strong proficiency in machine learning (ML), data science, and deep learning techniques.
○ Hands-on experience with Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
○ Experience with data preprocessing, feature engineering, and data
visualization.
○ Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI and ML deployment.
○ Strong analytical and problem-solving skills.
○ Ability to translate AI research into practical applications and solutions.
○ Knowledge of AI model evaluation techniques and performance optimization.
○ Strong communication skills for presenting research and technical details to non- technical stakeholders.
○ Ability to work independently and in team environments.
Preferred Qualifications
● Experience working with natural language processing (NLP), computer vision, or reinforcement learning.
What You’ll Be Doing
- Stay at the forefront of AI research to continually bring the latest innovations into our development pipeline. Your role will focus on experimenting with AI Agents and agentic AI, exploring how these technologies can enhance insurance workflows.
- Rapidly prototype and validate your ideas, demonstrating feasibility and potential impact. Work with large, complex datasets to develop models that solve real business challenges.
- While the core of your role is research-oriented, collaboration with production teams is essential. You will provide them with tested, validated concepts and support the initial stages of production integration.
- Partner with software developers, product managers, and other data scientists to ensure AI solutions are aligned with business needs
- Leverage state-of-the-art AI tools, frameworks, and libraries to accelerate AI development.
- Document AI research outcomes, development processes, and performance metrics. Present findings to stakeholders in an easily understandable manner.
PythonWhat We’re Looking For
Proven experience as a Machine Learning Engineer, Data Scientist, or similar role
Expertise in applying machine learning algorithms, deep learning, and data mining techniques in an enterprise environment
Strong proficiency in Python (or other languages) and familiarity with libraries such as Scikit-learn, TensorFlow, PyTorch, or similar.
Experience working with natural language processing (NLP) or computer vision is highly desirable.
Understanding and experience with (MLOps), including model development, deployment, monitoring, and maintenance.
Experience with cloud platforms (like AWS, Google Cloud, or Azure) and knowledge of deploying machine learning models at scale.
Familiarity with data architecture, data engineering, and data pipeline tools.
Familiarity with containerization technologies such as Docker, and orchestration systems like Kubernetes.
Knowledge of the insurance sector is beneficial but not required.
Bachelor's/Master's degree in Computer Science, Data Science, Mathematics, or a related field.
What You’ll Be Doing
Algorithm Development:
Design and implement advanced machine learning algorithms tailored for our datasets.
Model Creation:
Build, train, and refine machine learning models for business integration.
Collaboration:
Partner with product managers, developers, and data scientists to align machine learning solutions with business goals.
Industry Innovation:
Stay updated with Insurtech trends and ensure our solutions remain at the forefront.
Validation:
Test algorithms for accuracy and efficiency, collaborating with the QA team.
Documentation:
Maintain clear records of algorithms and models for team reference.
Professional Growth:
Engage in continuous learning and mentor junior team members.
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