Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest in the USA and has employees who live across the country. As we expand our global footprint with a new presence in Hyderabad, India, we’re building a world-class team to help us scale this mission and Clinical Intelligence and AI Evaluation is at the heart of everything we do. This job requires daily onsite work at our headquarters in Hyderabad, India.

Who We Need

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

This Opportunity

This Clinical Data Analyst position is a high impact, intellectually challenging role that requires a diverse set of analytical and technical skills. It provides unique opportunities for growth using an unprecedented amount of high-quality real-word Electronic Health Record (EHR) data and clinical notes data and become a nexus of healthcare and technology. You will be solving meaningful and consequential problems in healthcare using an EHR and clinical notes database of 120 million US patients (and growing!) and help drive insights that can ultimately improve and impact on patient care. This position will report to our Director of Clinical Intelligence and AI Evaluation team and support end-to-end evaluation, extraction, execution and delivery of custom concepts from clinical notes and EHR data to help our customers dive deeply into complex research questions related to human health and generate data-driven insights that support impactful scientific decisions.

Responsibilities

· Use technical skills to scope out clinical informatics data analyses requests from both internal and external customers, produce studies and results within an agreed deadline.

· Communicate on the status of various projects and collaborate with multidisciplinary stakeholders to ensure that clinical data projects are successfully executed and delivered.

· Excel in providing technical analytics support as well as directly working with internal stakeholders to troubleshoot any data analyses. Work with customers to achieve their goals, teaching them how to wrangle and analyze data using SQL, R and Python on real-world data to address their empirical questions.

· Write Databricks SQL queries to extract, analyze and interpret clinical concepts from clinical notes per customer requests.

· Create dashboards, data visualizations, and data tools to support data-driven decision making.

· Create enablement materials and studies as the Truveta platform evolves to help new researchers to increase our capabilities.

· Collaborate closely with other Truveta teams to conduct investigations of data sources to demonstrate veracity to current internal and external customers.

· Deliver feedback to internal teams based on customer requests to inform Truveta’s product roadmap.

Required Skills

· Graduate or Masters level educational degree in clinical research, data analysis, data science, clinical informatics, health information management or related fields.

· 3+ years of demonstrated experience conducting analyses using large healthcare datasets (e.g., electronic health records, clinical notes or other real-world data sources consisting of millions of patients' data.).

· 3+ years of demonstrated experience working with customers or research teams to translate their asks into executable analytical code, rigorous quality analytical datasets, deliver high quality research analyses.

· Strong proficiency in SQL, at least one statistical programming language (R or Python), familiar with Spark bigdata analytics environments, for data wrangling, analysis, and reproducible research workflows.

· Strong hands-on problem-solving skills, troubleshoot and identify data or methodological issues early and communicate them effectively. Have ownership, accountability and reliability mindset.

· Excellent written and verbal communication skills, including the ability to clearly explain analytical approaches and findings to technical and non-technical stakeholders.

· Ability to learn and adapt quickly in a dynamic start-up environment and a good team-player.

· Willingness to learn new analytical tools, programming languages, and proprietary platforms used to analyze real-world data.

Preferred Qualifications

These qualifications are preferred but not required, please do not let them stop you from applying for this role. You will likely get the opportunity to learn how to do these more advanced analyses if you don’t already have experience with them.

· Spark/PySpark, Databricks experience

· Experience working with unstructured clinical data or natural language processing outputs

· Regex query writing experience

· Experience building cohort definitions or eligibility criteria for research studies

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. We are expanding our global footprint. Join us as we build an amazing company together.

We Offer:

· Interesting and meaningful work for every career stage

· Great benefits package

· Comprehensive benefits with strong medical, dental and vision insurance plans

· Professional development & training opportunities for continuous learning

· Work/life autonomy via flexible work hours and flexible paid time off

· Generous parental leave

· Regular team activities (virtual and in-person as soon as we are able)

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude people from some sections, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements

Opportunity Overview:

We are looking for a Data Engineer to build and optimize scalable data pipelines and analytical datasets on our AWS-based lakehouse platform.

• You will work with Apache Iceberg, AWS Glue, Athena, dbt, and Airflow to support reliable and efficient data processing for analytics and operational use cases.
• You will collaborate with senior engineers, analytics teams, and platform stakeholders to deliver production-grade data solutions.

What you’ll do:

• Develop and maintain batch data pipelines
• Build reusable ingestion and transformation workflows
• Build and maintain Apache Iceberg datasets
• Support schema evolution and partition optimization
• Optimize Athena queries and troubleshoot performance bottlenecks
• Implement data validation checks and monitoring
• Support production issue troubleshooting

Required Qualifications:

• 4–5 years of experience in data engineering
• Strong hands-on experience with Python, SQL, PySpark/Spark
• Experience with AWS S3, Glue, Athena
• Experience with DBT and Airflow (or equivalent)
• Familiarity with Apache Iceberg / Hudi / Delta
• Understanding of partitioning and Parquet optimization

Interview Process*:

1. Connect with Talent Acquisition 
2. Technical Round 1 
3. Technical Round 2
4. Final Round 

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

As a Staff Data Scientist, you will act as a senior technical leader and trusted advisor across multiple teams. You’ll guide stakeholders through the complexity of modern AI systems, with a particular focus on agentic AI architectures (including LangGraph, LangFuse, and related tooling), as well as broader machine‑learning strategy. This role blends deep technical expertise, consultative problem‑solving, and cross‑functional leadership. 

You will often support several initiatives simultaneously, helping teams understand feasibility, scope, and risk while shaping high‑impact AI solutions that align with business needs. You’ll also mentor junior colleagues, elevate data‑science practices, and contribute hands‑on to the development of production‑grade AI systems. 

What you'll do:

AI Consulting & Advisory 

• Partner with product, engineering, and business teams to translate ambiguous problems into clear AI opportunities. 

• Provide expert guidance on agentic AI, including workflow orchestration, evaluation, observability, and safety. 

• Assess the complexity, feasibility, and expected value of proposed AI initiatives, helping teams prioritise effectively. 

• Communicate trade‑offs, risks, and solution paths to both technical and non‑technical audiences. 

AI & ML Solution Design 

• Architect end‑to‑end AI systems that solve real business problems, from early discovery through deployment. 

• Design agent‑based workflows, retrieval‑augmented pipelines, and ML‑powered automation. 

• Define evaluation strategies, data requirements, and success metrics for AI features and products. 

• Collaborate with engineering teams to ensure solutions are scalable, maintainable, and aligned with platform strategy. 

Hands‑On Technical Work 

• Build prototypes, proof‑of‑concepts, and production‑ready components using Python, modern AI frameworks, and cloud tooling. 

• Develop and refine agentic AI workflows using LangGraph, LangChain, LangFuse, or similar frameworks. 

• Implement machine‑learning models, retrieval systems, and data pipelines where needed. 

• Contribute to internal libraries, tooling, and best practices for AI development. 

Leadership & Mentorship 

• Mentor junior and mid‑level data scientists, providing guidance on modelling, experimentation, and system design. 

• Lead technical discussions, design reviews, and cross‑team collaboration sessions. 

• Champion high standards for code quality, documentation, and reproducibility. 

• Help shape the long‑term AI strategy and technical roadmap, through your technical knowledge on the art of the possible, and the business problems our clients face. 

What you'll bring:

• Extensive experience in data science, machine learning, or applied AI, including hands‑on coding in Python and common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy. 

• Ability with prototyping frameworks such as Dash. 

• Good working understanding of code version control with Git. 

• Experience with big data tools, such as: Spark, Dask, or alternatives. 

• Strong understanding of agentic AI, orchestration frameworks, and LLM‑based system design. 

• Ability to evaluate project complexity, identify risks, and guide teams toward pragmatic solutions. 

• Experience designing and delivering AI systems in production environments. 

• Excellent communication skills and the ability to influence beyond your immediate team. 

• Great mentoring skills. 
• Comfort working across multiple projects and shifting priorities. 

Nice to Have 

• Experience with observability and evaluation tools such as LangFuse, Weights & Biases, or similar. 

• Familiarity with agentic evals and prompt‑engineering patterns. 

• Background in consulting, technical advisory, or cross‑functional leadership roles. 

• Experience with cloud platforms (AWS, GCP, Azure) and modern MLOps practices. 

Job Summary

As a Data Scientist, you will work within a cross-functional agile team contributing to the company's growth in a fast-moving environment. You will develop new tools and features by working closely with engineers, product managers, designers, and engineers. Ultimately, the goal is to help our users make smarter decisions. On top of that, you’ll have the support of a diverse, large team of data scientists working across all Brandwatch products to support your technical and career development. This role is open to people with a variety of professional and academic backgrounds and you can expect to develop your skills in a wide variety of techniques, including machine learning, statistical modelling, and computational linguistics.

Essential Duties and Responsibilities

Work with stakeholders to clarity and refine questions.

Collect, clean, and prepare data, generally this will be large volumes of text along with metadata and will often need to be handled with big data tools.

Build models to solve a range of different problems, such as text classification and clustering, automated insight generation, and time series analysis.

Develop evaluation methodologies, which will vary from those based around conventional classification metrics (such as precision and recall), to designing methods to evaluate how well your tool helps a user achieve a defined task.

Support engineers as your projects are shipped. Sometimes you will also help maintain and upgrade the tools and technologies you develop.

Perform other duties as required to support evolving business needs.

Minimum Required Qualifications

A good working knowledge of Python (or another modern programming language, with willingness to learn Python).

A solid understanding of statistics and/or machine learning.

Enjoy an experimental and iterative approach to building products.

An ability to communicate with non-technical stakeholders, or willingness to skill up in this area.

Preferred Qualifications

Working in a data science team.

Common data science libraries, such as Numpy, Scipy, Pandas, SKlearn, Spacy.

Big data tools, such as: Spark, Dask, MapReduce, or alternatives.

Cloud computing, for example: AWS EC2, S3.

Linux style shell commands.

Application prototyping frameworks such as Dash, or Shiny.

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Senior Data Engineer to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs.

You're excited about this opportunity because you will…

• Work with business partners and stakeholders to understand data requirements
• Work with engineering, product teams and 3rd parties to collect required data
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Develop and implement data quality checks, conduct QA and implement monitoring routines
• Improve the reliability and scalability of our ETL processes
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We're excited about you because…

• 5+ years of professional experience
• 3+ years experience working in data engineering, business intelligence, or a similar role
• Proficiency in programming languages such as Python/Java
• 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP
• Expert in Database fundamentals, SQL and distributed computing
• 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink.
• Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS platforms
• Excellent communication skills and experience working with technical and non-technical teams
• Knowledge of reporting tools such as Tableau, Superset and Looker
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

The Telemetry Platform team is the backbone of real-time intelligence at DoorDash. We are architecting a unified, multi-brand foundational platform that powers sub-second user intent detection and mission-critical product experimentation for millions of users globally. Our team manages the entire data lifecycle—from high-performance mobile/web SDKs to massive-scale ingestion stacks and complex event processing engines. We are currently transitioning to a cutting-edge ingestion stack, creating a drift-free instrumentation culture that turns raw behavioral signals into actionable business insights.

About the Role

We are looking for a platform-oriented Engineering Manager to lead a multi-disciplinary team of Full Stack and Data Infrastructure (Backend) engineers. In this role, you will play a pivotal part in building these teams from the ground up and driving the long-term technical strategy for global telemetry. You will oversee the development of everything from developer-facing web UIs for schema management to high-throughput backend systems that process billions of events. This is a unique opportunity to lead a team at the intersection of platform engineering and deep data infrastructure.

You’re excited about this opportunity because you will…

• Build and Scale Teams: You will lead the hiring, onboarding, and mentorship of a high-performing team of Full Stack and Data Infrastructure engineers.
• Drive Strategy: You will execute the roadmap for the Unified Telemetry platform, balancing immediate "quick wins" with long-term engineering excellence and global scalability.
• Bridge Frontend & Backend: You will manage the development of the Event Schema Design UI and ClickStream Event Inspector alongside the Complex Event Processing (CEP) and Enrichment Frameworks.
• Enable Global Impact: Your team’s work will directly enable real-time user intention detection (e.g., identifying checkout abandonment) and power the foundational data layers for DoorDash’s global analytics.
• Foster Culture: You will champion a culture of reliability, quality, and technical rigor, ensuring telemetry is a "winning edge" for the organization.

We’re excited about you because you have…

• Experience: 10+ years of experience in software engineering, with at least 2+ years of hands-on management experience leading high-growth teams.
• Full Stack & Infra Fluency: You have a strong understanding of both modern Front End frameworks (for internal tooling/governance UIs) and Data Infrastructure (high-throughput ingestion, distributed systems, and real-time processing).
• Technical Breadth: Familiarity with technologies like Go/Kotlin/Python, React, and large-scale data ecosystems such as Kafka, Spark Streaming, Flink, or Snowflake.
• Strategic Leadership: Proven ability to break down complex, large-scale systems into reusable components and clear execution plans.
• Cross-Functional Collaboration: Exceptional communication skills with a track record of partnering with Product, Data Science, and Platform teams to deliver global solutions.
• Education: B.S., M.S., or PhD in Computer Science or a related technical field

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. Team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Staff Software Engineer, Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs.

You’re excited about this opportunity because you will…

• Own critical data systems that support multiple products/teams
• Develop, implement and enforce best practices for data infrastructure and automation
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We’re excited about you because…

• 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects
• 6+ years experience working in data platform and data engineering or a similar role
• Proficiency in programming languages such as Python/Kotlin/Scala
• 4+ years of experience in ETL orchestration and workflow management tools like Airflow
• Expert in database fundamentals, SQL, data reliability practices and distributed computing
• 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kafka/Flink/Spark Streaming
• Excellent communication skills and experience working with technical and non-technical teams and knowledge of reporting tools 
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on June 20, 2024.

Please see the independent bias audit report covering our use of Covey here.

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. Team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Software Engineer, Data to be a technical powerhouse to help us scale our data reliability, data infrastructure, automation and tools to meet growing business needs.

You’re excited about this opportunity because you will…

• Own critical data systems that support multiple products/teams
• Develop, implement and enforce best practices for data infrastructure and automation
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We’re excited about you because…

• 3+ years of professional experience
• 3+ years experience working in data platform and data engineering or a similar role
• Proficiency in programming languages such as Python/Kotlin/Scala
• 3+ years of experience in ETL orchestration and workflow management tools like Airflow
• Expert in database fundamentals, SQL, data reliability practices and distributed computing
• 3+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kafka/Flink/Spark Streaming
• Excellent communication skills and experience working with technical and non-technical teams and knowledge of reporting tools 
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making across business teams and drive efficiency in our operations. Data is fundamental to DoorDash’s success, and this team plays a critical role in enabling high-impact, data-driven solutions across Product, Operations, Finance, and more.

About the Role

As an Analytics Engineer, you’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives; working alongside Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.

This is a highly technical role where you'll be a driving force behind the analytics stack, delivering trusted data and metrics that support decision-making at all levels of the company. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you!

You’re excited about this opportunity because you will…

• Collaborate with data scientists, data engineers, and business stakeholders to understand business needs, and translate that scope into data requirements
• Identify key business questions and problems to solve for, and generate insights by developing structured solutions to resolve them
• Lead the development of data products and self-serve tools that enable analytics to scale across the company
• Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts
• Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode
• Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization

We’re excited about you because…

• 5+ years of experience working in business intelligence, analytics engineering, data engineering, or a similar role
• Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala
• Expertise in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Sigma)
• Familiarity with database fundamentals (e.g., S3, Trino, Hive, Spark), and experience with SQL performance tuning
• Experience in writing data quality checks to validate data integrity (e.g., Pydeequ, Great Expectations)
• Excellent communication skills and experience working with technical and non-technical teams
• Comfortable working in fast fast-paced environment, self-starter, and self-organizer
• Ability to think strategically, analyze, and interpret market and consumer information

Nice to Have

• Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance
• Experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster, DBT)
• Familiarity with experimentation concepts like A/B testing and their data requirements

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Opportunity Overview

As the Manager, Machine Learning & Data Science, you will play a key role in building and scaling Cohere Health’s AI capabilities in India. You’ll lead a team of machine learning engineers and data scientists focused on developing and deploying models that automate and augment complex clinical and administrative workflows.

This team is responsible for the full lifecycle of applied machine learning and data science—from problem framing and experimentation to production model deployment and ongoing optimization. You’ll work with structured and unstructured healthcare data to generate insights and power intelligent systems that improve prior authorization and broader clinical decision-making.

As a player-coach, you’ll combine hands-on technical contributions with team leadership, helping to establish best practices, mentor team members, and drive high-impact solutions in close partnership with Product, Engineering, Clinical, and Analytics stakeholders. This is an opportunity to shape both the technical direction and team culture within a growing global organization.

What you’ll do:

• Lead, mentor, and develop a team of machine learning engineers and data scientists, fostering a collaborative, high-performance environment
• Act as a hands-on contributor across the ML/DS lifecycle, including data exploration, feature engineering, model development, evaluation, and deployment
• Design, develop, and deploy machine learning models for retrieval, classification, and generative use cases across structured and unstructured data
• Translate complex business and clinical problems into scalable machine learning and data science solutions
• Establish and uphold best practices for experimentation, model validation, performance tracking, and reproducibility
• Partner cross-functionally with Product, Engineering, Clinical, and Analytics teams to align solutions with business priorities
• Guide the development of scalable data science and machine learning systems, including data preprocessing pipelines and production workflows
• Monitor model performance, identify opportunities for improvement, and drive continuous iteration and optimization
• Communicate technical concepts, methodologies, and insights clearly to both technical and non-technical stakeholders
• Contribute to hiring and scaling the team in India, including recruiting, onboarding, and coaching team members 

What you’ll need:

Must-haves

• Minimum 8+ years of experience in machine learning, data science, or applied AI roles, of those a minimum 2+ years of experience must be leading technical teams
• Strong hands-on experience building, evaluating, and deploying machine learning models in production
• Solid foundation in statistical methods, experimental design, and model evaluation
• Proficiency in Python and experience with ML frameworks (e.g., PyTorch, scikit-learn)
• Experience working with large, complex datasets (structured and/or unstructured)
• Strong problem-solving skills with the ability to translate business challenges into analytical solutions
• Excellent communication skills, with the ability to present complex concepts clearly to diverse stakeholders
• Experience working in fast-paced, evolving environments

Nice-to-haves

• Experience in healthcare, particularly with payer, provider, or clinical data
• Experience with NLP, deep learning (e.g., transformers), or generative AI (e.g., RAG)
• Familiarity with MLOps practices and production ML systems
• Experience with Spark or large-scale data processing frameworks
• Exposure to cloud platforms (e.g., AWS, SageMaker)
• Experience working in a global or distributed team environment
• Prior experience in a GCC or building teams in India

Interview Process*:

1. Connect with Talent Acquisition 
2. Meet with the Hiring Manager
3. Behavioral Interview(s)
4. Case Study
5. Interview with Senior Leadership

*Subject to change

About Cohere Health:

Cohere Health’s clinical intelligence platform delivers AI-powered solutions that streamline access to quality care by improving payer-provider collaboration, cost containment, and healthcare economics. Cohere Health works with over 660,000 providers and handles over 12 million prior authorization requests annually. Its responsible AI auto-approves up to 90% of requests for millions of health plan members.

With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.

Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn™ Startup for 2023 & 2024. Backed by leading investors such as Deerfield Management, Define Ventures, Flare Capital Partners, Longitude Capital, and Polaris Partners, Cohere Health drives more transparent, streamlined healthcare processes, helping patients receive faster, more appropriate care and higher-quality outcomes.

The Coherenauts, as we call ourselves, who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone.

We can’t wait to learn more about you and meet you at Cohere Health!

Equal Opportunity Statement: 

Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.

Job Overview 

We are looking for a bright and exceptional Engineering Lead to join our Technology team. In this role, you will work closely with Product Managers, Subject Matter Experts, Data Scientists and Software Engineers to design, build, and optimize scalable data pipelines for our Data Platform. The ideal candidate has strong hands-on experience in distributed data processing, expertise in architecting Data Pipelines and operational skills to drive efficiency and speed.

Key Responsibilities:

• Work closely with the product and other teams to understand business requirements and translate them into robust engineering solutions.
• Architect, build and maintain data solutions and pipelines to meet business requirements.
• Engage and lead a team of talented technologists and establishing engineering best practices.
• Act as a point of contact for managing and driving production defects & stability improvements to resolution
• Oversee end-to-end data workflows from ingestion, transformation, and storage to data lake in both batch and streaming environments.
• Drive improvements in performance, reliability, and scalability of data pipelines 

Required Skills & Qualifications:

• A bachelor’s degree in computer science, Math, or other technical fields with 6-8 years of experience, Fintech domain is a plus.
• Demonstrated contribution to end-to-end delivery of enterprise-grade software
• Experience on Data Engineering, Data Lakes, Data Warehousing, Data Pipelines, Data Analytics tools.
• Experience using open-source Big Data technologies such as Spark, Hadoop, Elasticsearch, Kafka.
• Hands-on experience in enterprise application development
• Strong SQL skills and experience working with relational and NoSQL databases.
• Experience in cloud technologies is a plus
• Demonstrates advanced proficiency in Python for building scalable data pipelines, automating workflows
• Experience building scalable ETL/ELT data pipelines and data lakes/warehouses.
• Familiarity with workflow orchestration tools (Airflow, ADF, Glue Workflow, etc.).
• Solid understanding of CI/CD, version control, and DevOps practices.
• Experience working in agile, collaborative environments.
• Attention to detail and quality, and the ability to work well in and across teams
• Ability to advocate & influence multiple stakeholders
• Excellent problem-solving, communication, and leadership skills.
• Experience in leading a team of highly skilled engineers

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

Job Title: Senior Data Engineer

Job Location: Hyderabad, India

Job Type: Full-time

Work Mode: (Hybrid – we operate from the office 1 day a week as of now and might change to 2 days depending on the need).

Company : Coeo Ltd.,

About the company: 

Coeo are trusted data management and analytics experts, delivering technology strategy and support for business. The team have deep technical and comraderies experience working with Microsoft Data Services to help our clients optimize their costs and maximize the benefits from their investments in these technologies. Coeo has been established for over 17 years and has offices in Reading, UK and Hyderabad, India. We are exclusively focused on Microsoft technologies. Our mission is to “help our clients predict their future” through the better use of data, technology, people, and processes. To do this our business has always focused on:

• Data Managed Services
• Data Platform Consultancy
• Analytics Consultancy
• Artificial Intelligence Consultancy
• Adoption and Change Management

But above all, Coeo’s most important asset is its people, and at Coeo we are really focused on investing time, attention, and resources into building a culture that truly values its people.

We are growing our teams in India to support our ongoing customer requirements in Managed Services, Consulting and Development.

Coeo is recruiting a strong Senior Data Engineer; we’ll give you the opportunity to grow and develop your capabilities as well as support you through Microsoft certifications. You’ll have experience in:

• Developing low to high complexity, secure, governed, high quality and efficient data pipelines from a variety of on and off premise, internal and external data sources.
• Ensuring that data is cleansed, mapped, transformed, and optimized for storage to meet requirements for business and technical use cases.
• Building data observability and data quality by design into all Data pipelines, promoting self-testing pipelines that proactively identify processing issues or discrepancies.
• Take all requirements into account when creating a proposal
• Understanding and evaluating the organizational impact of new technologies and digital services
• Troubleshooting and resolving issues

You may be building solutions that transform data into data lake storage areas, physical database models and reporting structures across data lakes, Datawarehouse, business intelligence systems and analytics applications. You may also be required to carry out unit testing of your own code and peer testing of others to ensure appropriate quality.

Experience

• Experience working with large, event-based, datasets in an enterprise environment.
• Minimum 6 years within an Azure or SQL Data Engineering environment
• Engineering and database skills in SQL Server and/or Azure (Data Factory, Synapse) and the associated ETL technologies.
• Experience developing, driving & maintaining Data Integration Roadmaps and best practices.
• Overall responsibility of all technical business requirements, gathering deliverables and implementation.
• Ability to deliver high-to-low level designs for Data Solutions and have a good understanding of the full data lifecycle.
• Hands-on experience in designing and developing scripts for custom ETL processes and automation in Azure Data Factory, Azure Databricks, Azure Synapse, Python, Pyspark etc.
• Hands-on experience designing and developing stored procedures/functions and leveraging ETL packages/workflows
• Expertise in Cloud related Big Data integration and infrastructure tech stack using Azure Databricks & Apache Spark framework
• Well-versed with scripting languages such as Python
• Experience in Continuous Integration / Continuous Delivery (CI/CD).
• Experience working in an agile environment and self-managing teams.
• Understanding and practical knowledge of testing techniques and tools

Desired Skills

• Big Data
• Azure
• Spark
• Python
• Azure Databricks
• Azure Synapse
• Microsoft Fabric
• Azure Data Factory
• SQL Server

Benefits

• Company bonus scheme driven by yours and our success
• Comprehensive benefits package
• We care about your wellbeing so have invested resources and training help to ensure you can be at your best with us
• Very friendly, inclusive culture, family-feel and strong camaraderie
• Company growth and new projects mean on going career progression options
• Up to date technology, so collaboration has never been easier
• Cutting edge technology projects – exciting goals ahead!

Diversity and Inclusion:

Coeo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We welcome applicants from all backgrounds and strive to ensure that everyone feels valued, respected, and supported. If you require any adjustments or additional support during the interview process, please let us know, and we will be happy to accommodate your needs.

How to Apply:

Click Apply or visit our Careers page at www.coeo.com. or you can send your resume to krishna.chaitanya@coeo.com

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

Overview:   The Staff Software Engineer L5 works with all service aspects of high throughput and multi-tenant services, has the ability to design components carefully, properly handle errors, write clean and well-factored code with good tests and good maintainability. 

Duties and Responsibilities:

• Design distributed systems that are resilient and secure at scale from inception;
• Raise the engineering bar on scale, resiliency, security fundamentals via technical leadership and engineering excellence;
• Discover, review, and influence new and evolving design, architecture, and standards for building and delivering unique services and solutions;
• Investigate, design, and implement best-in-industry, innovative technologies that will expand Inovalon’s infrastructure through robust, scalable, adrenaline-fueled solutions;
• Champion the enterprise infrastructure vision and strategy;
• Be the expert in service reliability and sustainability;
• Develop and execute designs for complex systems backed by excellence, confidence, and thorough engineering analysis;
• Develop, gather, and leverage metrics to manage the server fleet and complex computing systems to drive automation, improvement, and performance;
• Take ownership of ensuring detailed design, analysis, testing, and optimization;
• Set direction/goals for the team regarding project impact, product quality and engineering efficiency;
• Lead major initiatives, projects, teams, rollouts and phased releases;
• Provide mentorship onboarding new team members and enabling successful ramp up;
• Collaborate with other engineers, services across Inovalon, and external customers to understand requirements, have tight feedback loop that is data driven;
• Adhere to all confidentiality, HIPAA, regulatory, and other such policies, procedures, and requirements as outlined within Employer’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the scope of work.
• Maintain compliance with Inovalon’s policies, procedures and mission statement, and fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success.
• On Call Policy: Participate in an on-call rotation to support critical issues, including outside standard business hours (evenings, weekends, and holidays), ensuring timely response and resolution as per defined SLAs.

Job Requirements:

• Minimum 15 years of plus experience with Unix management, complex computing platforms, and/or cutting-edge technologies involving virtualization, distribution, and high performance computing;
• Strives to achieve excellence backed by strong architectural, system design, and automation experience;
• Technology experience required; Hive, Hbase, Sqoop, Ranger, NIFI - Other technologies good to have; Spark, Phoenix, Spring Batch, Accumulo, Falcon, Atlas;
• Experience engineering solutions on one of the major Hadoop distributions - Java scripting and application support experience strongly desired;
• Experience with virtualization technologies required and driven to solve difficult problems with scalable, elegant, and maintainable solutions;
• Expert and creative troubleshooter – unrelenting, persistent, confident;
• A penchant for thinking outside the box to solve complex and interesting problems;
• Extensive knowledge of existing industry standards, technologies, and infrastructure operations;
• Ability to manage stressful situations with calm, courtesy, and confidence;
• Experience building and shipping high quality work and achieving high reliability; and
• Experience improving stability through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes.

Education:

• Bachelor's degree in computer science, Software Engineering, or Information Technology

Physical Demands and Work Environment:

• Sedentary work (i.e. sitting for long periods of time).
• Exerting up to 10 pounds of force occasionally and/or negligible amount of force.
• Subject to inside environmental conditions.
• Travel for this position will include less than 10% locally usually for training purposes.

Overview:   The Staff Software Engineer L5 works with all service aspects of high throughput and multi-tenant services, has the ability to design components carefully, properly handle errors, write clean and well-factored code with good tests and good maintainability. 

Duties and Responsibilities:

• Design distributed systems that are resilient and secure at scale from inception;
• Raise the engineering bar on scale, resiliency, security fundamentals via technical leadership and engineering excellence;
• Discover, review, and influence new and evolving design, architecture, and standards for building and delivering unique services and solutions;
• Investigate, design, and implement best-in-industry, innovative technologies that will expand Inovalon’s infrastructure through robust, scalable, adrenaline-fueled solutions;
• Champion the enterprise infrastructure vision and strategy;
• Be the expert in service reliability and sustainability;
• Develop and execute designs for complex systems backed by excellence, confidence, and thorough engineering analysis;
• Develop, gather, and leverage metrics to manage the server fleet and complex computing systems to drive automation, improvement, and performance;
• Take ownership of ensuring detailed design, analysis, testing, and optimization;
• Set direction/goals for the team regarding project impact, product quality and engineering efficiency;
• Lead major initiatives, projects, teams, rollouts and phased releases;
• Provide mentorship onboarding new team members and enabling successful ramp up;
• Collaborate with other engineers, services across Inovalon, and external customers to understand requirements, have tight feedback loop that is data driven;
• Adhere to all confidentiality, HIPAA, regulatory, and other such policies, procedures, and requirements as outlined within Employer’s Operating Policies and Procedures in all ways and at all times with respect to any aspect of the data handled or services rendered in the scope of work.
• Maintain compliance with Inovalon’s policies, procedures and mission statement, and fulfill those responsibilities and/or duties that may be reasonably provided by Inovalon for the purpose of achieving operational and financial success.
• On Call Policy: Participate in an on-call rotation to support critical issues, including outside standard business hours (evenings, weekends, and holidays), ensuring timely response and resolution as per defined SLAs.

Job Requirements:

• Minimum 15 years of plus experience with Unix management, complex computing platforms, and/or cutting-edge technologies involving virtualization, distribution, and high performance computing;
• Strives to achieve excellence backed by strong architectural, system design, and automation experience;
• Technology experience required; Hive, Hbase, Sqoop, Ranger, NIFI - Other technologies good to have; Spark, Phoenix, Spring Batch, Accumulo, Falcon, Atlas;
• Experience engineering solutions on one of the major Hadoop distributions - Java scripting and application support experience strongly desired;
• Experience with virtualization technologies required and driven to solve difficult problems with scalable, elegant, and maintainable solutions;
• Expert and creative troubleshooter – unrelenting, persistent, confident;
• A penchant for thinking outside the box to solve complex and interesting problems;
• Extensive knowledge of existing industry standards, technologies, and infrastructure operations;
• Ability to manage stressful situations with calm, courtesy, and confidence;
• Experience building and shipping high quality work and achieving high reliability; and
• Experience improving stability through thoughtful code reviews, appropriate testing, proper rollout, monitoring, and proactive changes.

Education:

• Bachelor's degree in computer science, Software Engineering, or Information Technology

Physical Demands and Work Environment:

• Sedentary work (i.e. sitting for long periods of time).
• Exerting up to 10 pounds of force occasionally and/or negligible amount of force.
• Subject to inside environmental conditions.
• Travel for this position will include less than 10% locally usually for training purposes.

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad 

Lead Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 10+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 10+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.

• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Hyderabad 

Senior Data Scientist

What You Can Expect from Us:

Here at NomiSo, we work hard to provide our team with the best opportunities to grow their careers.  You can expect to be a pioneer of ideas, a student of innovation, and a leader of thought. Innovation and thought leadership is at the center of everything we do, at all levels of the company. Let’s make your career great!

Position Overview: 

We are looking for an experienced Data Scientist with a strong academic background in Data Science and 8+ years of hands-on experience in Data science projects. The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning and AI techniques to solve complex business problems.

Roles and Responsibilities:

• Analyze large datasets to extract meaningful insights and patterns.
• Develop, implement, and optimize ML/AI models for predictive and prescriptive analytics
• Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.
• Design and build data pipelines and perform data wrangling using Python, R, or SQL.
• Communicate analytical findings through clear data visualizations and storytelling techniques.
• Evaluate model performance and improve accuracy and efficiency.
• Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML/AI models in production.
• Ensure data quality, governance, and compliance with organizational standards.
  
  

Must Have Skill

• 8+ years of relevant experience in Data Science Machine Learning / AI projects.
• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.
• Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.
• Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.
• Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.).
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.
• Excellent analytical, problem-solving, and communication skills.
  
  

Good To Have:

• Experience with Deep Learning, NLP, or Time Series Analysis.
• Exposure to MLOps and CI/CD pipelines for model deployment.
• Certifications or project portfolios in Data Science or Machine Learning
• Experience in prompt engineering, context / RAG engineering, Agentic AI.
  
  

Qualification:

• Bachelor’s or Master’s or PhD degree in Data Science, or a related discipline.

Location:   Pune / Hyderabad