Current Opening for Cognitio Analytics
Position
Location
Experience
Overview
We are looking for a skilled Sr QA Automation Engineer with 3–5 years of experience in Functional and automation testing. The candidate will be responsible for designing, developing, and maintaining automated test scripts to ensure high-quality software delivery. You will collaborate closely with Engineering team, product managers, and QA teams to identify test scenarios and improve testing efficiency.
Must have: 3–5 years of experience in Functional Testing with hands-on Automation (Selenium/Cypress/Playwright), proficiency in Java/Python/JavaScript, API Testing (Postman/REST Assured), Test-Frameworks (TestNG/JUnit/Mocha), Git, and strong understanding of SDLC/STLC & Agile.
Good to Have: Experience with BDD (Cucumber), CI/CD tools (Jenkins/GitHub Actions/GitLab CI), Performance Testing (JMeter), Cloud platforms (AWS/Azure), and Microservices architecture.
Key Responsibilities
- Design, develop, and maintain automated test frameworks and test scripts.
- Perform functional, regression, integration, and system testing.
- Develop automation scripts using tools like Selenium, Cypress, Playwright, or Appium.
- Collaborate with Engineering teams to understand requirements and create test cases and test plans.
- Execute automated and manual test cases and report defects using tools like JIRA, Azure DevOps, or Bugzilla.
- Integrate automated tests into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
- Participate in Agile/Scrum ceremonies such as sprint planning, stand-ups, and retrospectives.
- Monitor test execution and provide detailed test reports and quality metrics.
- Continuously improve test automation frameworks and testing processes.
Education
Bachelor’s degree in computer science, Information Technology, or related field.
“Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.”
About the Role
As a Full-Stack Machine Learning Engineer, you will design and deploy ML-driven applications that enhance claims processing, fraud detection, and customer experience. You’ll work across backend services, ML pipelines, and front-end interfaces to deliver secure, scalable, and compliant solutions.
Key Responsibilities
•ML solutions: Develop and deploy predictive models for risk scoring, claims automation, fraud detection, and personalization.
•Backend services: Build robust APIs using Java/Kotlin (Spring Boot or Ktor) for model inference and integration with insurance platforms.
•Data pipelines: Design and optimize ETL/ML workflows in Databricks or Spark, ensuring compliance with data governance and regulatory standards.
•Frontend: Create intuitive React.js dashboards for underwriters, claims teams, and business users to visualize model outputs and KPIs.
•Database management: Work with PostgreSQL databases to store policy, claims, and model metadata securely.
•Model deployment & monitoring: Implement production-grade deployment strategies with drift detection, audit trails, and rollback mechanisms.
•Compliance & security: Ensure solutions adhere to insurance regulations (e.g., MAS, GDPR) and internal security policies.
•Cross-functional collaboration: Communicate effectively with actuaries, data scientists, and business stakeholders.
•Amplify Health confidential and proprietary information. Do not distribute.
Required Qualifications
•3–5 years of experience in ML engineering with exposure to insurance or financial services preferred.
•Strong programming skills in Java or Kotlin; experience with Spring Boot/Ktor for API development.
•Hands-on with Databricks and Spark for large-scale data processing.
•Proficient in React.js for building user interfaces.
•Solid understanding of SQL and data modeling for transactional and analytical systems.
•Experience deploying ML models in production with monitoring and governance.
•Excellent communication skills to explain technical concepts to non-technical teams.
Nice-to-Have
•Knowledge of insurance workflows (claims, fraud detection).
•Familiarity with regulatory compliance frameworks (GDPR, MAS guidelines).
•Experience with MLflow, feature stores, and model explainability tools.
•Exposure to cloud platforms (AWS/Azure/GCP) and containerization (Docker/Kubernetes).
“Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.”
Role Overview
We are hiring a Lead Data Scientist – Implementation Lead. This role owns end-to-end delivery and implementation of data science solutions, leads teams, sets up SOPs, and ensures scalable, repeatable execution. Development Leads and Implementation Leads will report into this role.
Key Responsibilities
- Own end-to-end implementation of data science and AI initiatives
- Lead and manage a team of Data Scientists and Implementation Leads
- Set up, document, and improve SOPs for delivery and implementation
- Drive NLP and ML-based solution execution
- Use GenAI tools (LLMs, copilots, prompt-based tools) to improve productivity and delivery
- Collaborate with product, engineering, and business teams to ensure on-time, high-quality delivery
Must-Have Skills & Experience
- 6–10 years of experience in Data Science / Applied AI roles
- Strong Python programming skills (pandas, NumPy, advanced Python concepts)
- Hands-on NLP experience
- Proven experience in team management and end-to-end ownership
- Experience creating and maintaining SOPs (product company experience preferred)
- Strong communication and stakeholder management skills
- Good to Have
- Cloud experience (Azure preferred – Databricks, Synapse, Data Factory)
- MLOps exposure (FastAPI, Docker)
- Experience in enterprise or product-led environments
“Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.”
Core responsibilities include:
· Owning and executing distinct work streams within larger analytics engagement
· Delivering insights based on complex data analysis, within relevant verticals
(insurance, health care, banking, etc.)
· Hands on experience in data manipulation/processing skills using Python.
· Experience in exploratory data analysis and feature engineering
· Must have strong capabilities in problem solving, managing own work diligently,
thoroughly documenting own work, succinctly communicating analysis process and
outcomes, as well as effectively working with clients
· Basic understanding of at least one business area and its components (Healthcare,
Insurance, Banking, Telecommunications, Logistics)
· Familiarity with / Exposure on cloud engineering (preferred)
· Ability to translate technical information to non-technical stakeholders and vice versa
· Strong verbal and written communications skills
· Actively seeks information to clarify customer needs to deliver better experience
· Acts promptly to ensure customer needs are fulfilled
What skills do you need?
Behavioral skills
• Exceptional communication skills across a wide range of stakeholders
• Ability to work cohesively in a team environment while balancing multiple
priorities.
• High level of attention to detail, resilience, enthusiasm, energy and drive
• Positive, can-do attitude focused on continuous improvement
• Ability to take feedback and constructive criticism to drive improved delivery
• Rigorous ability to solve complex analytical problems, optimize environments
and communication with stakeholders
• Good time management, co-ordination and communication skills
• Strong problem-solving
Technical Skills
A deep understanding of the technical tools used in analytical domain is required as the
bases for development of analytical products, as such the following core
understandings are required:
Excellent Microsoft Excel
SQL & PySpark are must
Strong analytical things
Strong problem solving
PowerBI – Intermediate level is required
Strong communication & ability to exchange thoughts
Strong understanding of business and ability to read between the lines.
Comfortable to work with large data sets.
• Excellent experience in writing code in SQL, python/Pys park
• Good to have Power BI (should be able to develop Power BI Dashboard and
Maintenance)
• Advanced excel in the context of data exploration and manipulation.
• Knowledge of cloud technologies such as data bricks, azure studio, data factory,
etc. (preferred)
• Understanding of large data and exceptional data sense is mandatory
• Any knowledge of data or patient health management, provider profiling,
healthcare reporting, and other key healthcare technologies etc. is beneficial but
not required.
• Prior experience with clients is preferred
• Healthcare background is preferred.
Qualifications
• Bachelor’s degree in engineering, Data Science, Statistics, Mathematics, or
related quantitative field.
• MBA graduate from a Tier-1 institute or a master’s degree in relevant field
• Minimum 2 years of experience in data and analytics and stakeholder
management.
Additional key skills we are looking at
Stakeholder Management, Client Communication, Team Management, Project
Management, Problem Solving, Python, SQL, Storytelling, Presentation Skills
“Cognitio Analytics is an equal-opportunity employer. We are committed to a work
environment that celebrates diversity. We do not discriminate against any individual
based on race, color, sex, national origin, age, religion, marital status, sexual
orientation, gender identity, gender expression, military or veteran status, disability, or
any factors protected by applicable law. All Cognitio employees are expected to
understand and adhere to all Cognitio Security and Privacy related policies in order to
protect Cognitio data and our client’s data. Our salary ranges are based on paying
competitively for our size and industry and are one part of the total compensation
package that also includes a bonus plan, equity, benefits, and other opportunities at
Cognitio. Individual pay decisions are based on a number of factors, including
qualifications for the role, experience level, and skillset.”
Ideal qualifications, skills and experiences we are looking for are:
- We are actively seeking a talented and results-driven Data Scientist to join our team and take ownership of deliverables through the power of data analytics and insights.
- Your contributions will be instrumental in making data-informed decisions, identifying growth opportunities, and propelling our organization to new levels of success.
- Doctorate/Master’s/bachelor’s degree in data science, Statistics, Computer Science, Mathematics, Economics, commerce or a related field.
- Minimum of 3 years of experience working as a Data Scientist or in a similar analytical role, with experience leading data science projects and teams.
- Experience in Healthcare domain with exposure to clinical operations, financial, risk rating, fraud, digital, sales and marketing, and wellness, e-commerce or the ed tech industry is a plus.
- Expertise in programming languages such as SQL, Python/PySpark and proficiency with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, Matplotlib, seaborn).
- Very strong python and exceptional with pandas, NumPy, advanced python (pytest, class, inheritance, docstrings).
- Deep understanding of machine learning algorithms, model evaluation, and feature engineering. Experience with frameworks like scikit-learn, TensorFlow, or Py torch.
- Deep understanding of ML and Deep Learning is a must
- Basis NLP experience is highly valuable.
- Pyspark experience is highly valuable.
- Competitive coding experience (LeetCode) is highly valuable.
- Strong expertise in statistical modelling techniques such as regression, clustering, time series analysis, and hypothesis testing.
- Experience of building & deploying machine learning models in cloud environment: Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.)
- Basic MLOPs experience with FastAPIs and experience of docker is highly valuable and AI governance
- Ability to understand business objectives, market dynamics, and strategic priorities. Demonstrated experience translating data insights into tangible business outcomes and driving data-informed decision-making.
- Excellent verbal and written communication skills
- Proven experience leading data science projects, managing timelines, and delivering results within deadlines.
- Strong collaboration skills with the ability to work effectively in cross-functional teams, build relationships, and foster a culture of knowledge sharing and continuous learning.
Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.
Ideal qualifications, skills and experiences we are looking for are:
- We are actively seeking a talented and results-driven Data Scientist to join our team and take on a leadership role in driving business outcomes through the power of data analytics and insights.
- Your contributions will be instrumental in making data-informed decisions, identifying growth opportunities, and propelling our organization to new levels of success.
- Doctorate/Master’s/bachelor’s degree in data science, Statistics, Computer Science, Mathematics, Economics, commerce or a related field.
- Minimum of 6 years of experience working as a Data Scientist or in a similar analytical role, with experience leading data science projects and teams.
- Experience in Healthcare domain with exposure to clinical operations, financial, risk rating, fraud, digital, sales and marketing, and wellness, e-commerce or the ed tech industry is a plus.
- Proven ability to lead and mentor a team of data scientists, fostering an innovative environment. Strong decision-making and problem-solving skills to guide strategic initiatives.
- Expertise in programming languages such as Python and R, and proficiency with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, Matplotlib, seaborn).
- Very strong python and exceptional with pandas, NumPy, advanced python (pytest, class, inheritance, docstrings).
- Deep understanding of machine learning algorithms, model evaluation, and feature engineering. Experience with frameworks like scikit-learn, TensorFlow, or Py torch.
- Experience of leading a team and handling projects with end-to-end ownership is a must
- Deep understanding of ML and Deep Learning is a must
- Basis NLP experience is highly valuable.
- Pyspark experience is highly valuable.
- Competitive coding experience (LeetCode) is highly valuable.
- Strong expertise in statistical modelling techniques such as regression, clustering, time series analysis, and hypothesis testing.
- Experience of building & deploying machine learning models in cloud environment: Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.)
- Basic MLOPs experience with FastAPIs and experience of docker is highly valuable and AI governance
- Ability to understand business objectives, market dynamics, and strategic priorities. Demonstrated experience translating data insights into tangible business outcomes and driving data-informed decision-making.
- Excellent verbal and written communication skills
- Proven experience leading data science projects, managing timelines, and delivering results within deadlines.
- Strong collaboration skills with the ability to work effectively in cross-functional teams, build relationships, and foster a culture of knowledge sharing and continuous learning.
Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.
About Us:
Website: https://www.cognitioanalytics.com/
Cognitio Analytics, founded in 2013, aims to be the preferred provider of AI / ML driven productivity solutions for large enterprises. The company has received awards for its Smart Operations and Total Rewards Analytics Solutions and is dedicated to innovation, R&D, and creating sustained value for clients. Cognitio Analytics has been recognized as a “Great Place to Work” for its commitment to fostering an innovative work environment and employee satisfaction.
Our solutions include Total Rewards Analytics powered by Cognitio’s Total Rewards Data Factory, The Total Rewards Analytics solutions help our clients achieve better outcomes and higher ROI on investments in all kinds of Total Rewards programs.
Our smart operations solutions drive productivity in complex operations, such as claims processing, commercial underwriting etc. These solutions, based on proprietary capabilities based on AI, advanced process and task mining, and deep understanding of operations drive effective digital transformation for our clients.
Experience: 3 – 5 years
Job Description:
We are seeking a highly skilled Azure Cloud Data Engineer to join our dynamic team. As an Azure Cloud Data Engineer, you will be responsible for designing, implementing, and managing cloud-based data solutions using Microsoft Azure. The ideal candidate should have a strong background in data engineering, with hands-on experience in Azure services and tools.
Skill Required:
Must Haves:
- Exp in Data Engineering domain: 2+ Years.
- SQL, Python, Py Spark.
- Spark, Distributed Systems.
- Azure Databricks, Azure Data Factory,ADLS Gen 2 Blob Storage, Key Vaults, Azure DevOps.
- ETL, Building Data Pipelines, Data Warehousing, Data Modelling and Governance.
- Agile Practices, SDLC
- Multi years’ experience with Azure-Databricks ecosystem and Py spark.
- Ability to write clean, concise and organized Py spark code.
- Ability to break down the project into executable steps, prepare a DFD and execute the same
- Propose innovative DE solutions to achieve business objectives.
- Quick on his feet, good at tech and logically complex communication
- Good Knowledge of ADF, Docker /containerization.
Good to Have:
- Event Hubs, Logic Apps.
- Power BI
- Competitive coding and knows most Py spark syntax by heart.
Essential Job Duties & Responsibilities:
- Set up workflows and orchestration processes to streamline data pipelines and ensure efficient data movement within the Azure ecosystem.
- Create and configure compute resources within Databricks, including All-Purpose and SQL Compute and Job Clusters to support data processing and analysis.
- Set up and manage Azure Data Lake (ADLS) Gen 2 storage accounts and establish a seamless integration with Databricks Workspace for data ingestion and processing.
- Create and manage Service Principals, key vaults to securely authenticate and authorize access to Azure resources.
- Utilize ETL (Extract, Transform, Load) techniques to design and implement data warehousing solutions and ensure compliance with data governance policies.
- Develop highly automated ETL scripts for data processing.
- Scale infrastructure resources based on workload requirements, optimizing performance and cost-efficiency.
- Profile new data sources in a different format including CSVs, JSONs etc.
- Apply problem-solving skills to address complex business and technical challenges, such as data quality issues, performance bottlenecks, and system failures.
- Demonstrate excellent soft skills and the ability to effectively communicate and collaborate with clients, stakeholders, and cross-functional teams.
- Implement Continuous Integration/Continuous Deployment (CI/CD) practices to automate the deployment and testing of data pipelines and infrastructure changes.
- Delivering tangible value very rapidly, collaborating with diverse teams of varying backgrounds and disciplines.
- Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases.
- Manage timely appropriate communication and relationship with clients, partners and other stakeholders.
- Create and manage periodic reporting of project execution status and other trackers in standard accepted formats.
Required Competencies:
- Strong proficiency in SQL for data manipulation, querying, and optimization.
- Proficiency in Python and PySpark for data engineering and data processing tasks.
- Solid understanding of the Microsoft Azure tooling for large-scale data engineering efforts and deployments is highly preferred.
- Hands-on experience with Azure Databricks, including data ingestion, transformation, and analysis.
- Ability to set up and manage Azure Data Lake Storage (ADLS) Gen 2 accounts, and familiarity with data lake architecture and best practices.
- Knowledge of Azure Key Vaults for securely storing and managing cryptographic keys, secrets, and certificates.
- An ‘engineering’ mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact.
- Comfort with working with distributed teams on code-based deliverables, using version control systems and code reviews.
- Use of agile and DevOps practices for project and software management including continuous integration and continuous delivery.
- Ability to conduct data analysis, investigation, and lineage studies to document and enhance data quality and access.
- Proven track record of scaling infrastructure to meet performance and scalability requirements.
- Strong analytical and problem-solving skills, with the ability to troubleshoot complex technical issues.
- Direct experience having built and deployed robust, complex production systems.
- Proficiency in Event Hubs and Azure Data Factory, particularly in the context of data streaming and transfer.
Qualifications:
- Bachelor’s degree in computer science, Engineering, or a quantitative discipline.
- 3+ years of professional experience as an Azure Cloud Data Engineer or a similar role.
- Excellent communication skills, both verbal and written.
- Strong attention to detail and the ability to work in a fast-paced environment.
Core responsibilities include:
- Owning and executing distinct work streams within larger analytics engagement
- Delivering insights based on complex data analysis, within relevant verticals (insurance, health care, banking, etc.)
- Hands on experience in data manipulation/processing skills using Python.
- Experience in exploratory data analysis and feature engineering
- Must have strong capabilities in problem solving, managing own work diligently, thoroughly documenting own work, succinctly communicating analysis process and outcomes, as well as effectively working with clients
- Basic understanding of at least one business area and its components (Healthcare, Insurance, Banking, Telecommunications, Logistics)
- Familiarity with / Exposure on cloud engineering (preferred)
- Ability to translate technical information to non-technical stakeholders and vice versa
- Strong verbal and written communications skills
- Actively seeks information to clarify customer needs to deliver better experience
- Acts promptly to ensure customer needs are fulfilled
- Exceptional communication skills across a wide range of stakeholders
- Ability to work cohesively in a team environment while balancing multiple priorities.
- High level of attention to detail, resilience, enthusiasm, energy and drive
- Positive, can-do attitude focused on continuous improvement
- Ability to take feedback and constructive criticism to drive improved delivery
- Rigorous ability to solve complex analytical problems, optimize environments and communication with stakeholders
- Good time management, co-ordination and communication skills
- Strong problem-solving
- Strong experience is writing code in SQL, python/PySpark
- Advanced excel in the context of data exploration and manipulation.
- Knowledge of cloud technologies such as data bricks, azure studio, data factory, etc. (preferred)
- Understanding of large data and exceptional data sense is mandatory
- Any knowledge of data or patient health management, provider profiling, healthcare reporting, and other key healthcare technologies etc. is beneficial but not required.
- Prior experience with clients is preferred
- Healthcare background is preferred.
- Bachelor’s degree in engineering, Data Science, Statistics, Mathematics, or related quantitative field.
- MBA graduate from a Tier-1 institute or a master’s degree in relevant field
- Minimum 2 years of experience in data and analytics and stakeholder management.
Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.
Senior Machine Learning Engineer (Java + Python) (Contractual)
Gurugram (Hybrid)
8 To 10 years
About the Role
We are seeking a seasoned Senior Machine Learning Engineer to lead the design, development, and deployment of enterprise-grade ML solutions for insurance and financial services. This role combines deep technical expertise in Java and Python, architectural design, and team leadership to deliver scalable, secure, and compliant ML-driven applications. You will mentor engineers, define best practices, and collaborate with cross-functional teams to drive innovation in claims automation, fraud detection, and customer personalization.
Key Responsibilities
•Solution Architecture: Design end-to-end ML system architecture, including data pipelines, model serving infrastructure, and integration with enterprise platforms.
•ML Development: Build and deploy predictive models for risk scoring, fraud detection, and personalization using Python-based ML frameworks and Java/Kotlin for backend services.
•Backend Services: Architect and implement robust APIs using Spring Boot/Ktor and FastAPI for model inference and orchestration.
•Data Engineering: Oversee ETL and ML workflows in Databricks and Spark, ensuring scalability and compliance with data governance standards.
•Frontend Oversight: Guide development of React.js dashboards for business users to visualize KPIs and model outputs.
•Database Management: Define secure data models and manage PostgreSQL for transactional and analytical workloads.
•Deployment & Monitoring: Establish production-grade deployment strategies with CI/CD, drift detection, audit trails, and rollback mechanisms.
•Amplify Health confidential and proprietary information. Do not distribute.
•Compliance & Security: Ensure adherence to regulatory frameworks (MAS, GDPR) and internal security policies.
•Team Leadership: Mentor junior engineers, manage project timelines, and enforce coding standards and architectural best practices.
•Stakeholder Collaboration: Communicate technical strategies to executives, actuaries, and business teams effectively.
Required Qualifications
•8–10 years of experience in ML engineering, with at least 3 years in a leadership or architectural role.
•Strong programming skills in Java/Kotlin and Python; expertise in Spring Boot/Ktor and FastAPI.
•Proven experience designing ML architectures and deploying models at scale.
•Hands-on with Databricks, Spark, and distributed data processing.
•Solid understanding of SQL, data modeling, and database optimization.
•Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP).
•Excellent leadership and communication skills to manage teams and influence stakeholders.
Nice-to-Have
•Knowledge of insurance workflows (claims, fraud detection).
•Familiarity with ML governance tools (MLflow, feature stores, explainability frameworks).
•Exposure to microservices architecture and event-driven systems.
•Certification in cloud architecture or ML engineering.
“Cognitio Analytics is an equal-opportunity employer. We are committed to a work environment that celebrates diversity. We do not discriminate against any individual based on race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any factors protected by applicable law. All Cognitio employees are expected to understand and adhere to all Cognitio Security and Privacy related policies in order to protect Cognitio data and our client’s data. Our salary ranges are based on paying competitively for our size and industry and are one part of the total compensation package that also includes a bonus plan, equity, benefits, and other opportunities at Cognitio. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, and skillset.”
If you would like to apply for this position, please send your details to the following email address:
hr@cognitioanalytics.com