Opportunity Overview:

We are seeking a Technical, Hands-on Manager to lead a team in building AI-driven healthcare enterprise applications. In this role, you will combine strong people leadership with deep technical expertise to guide the development of scalable, data-intensive solutions that drive meaningful business impact.

As a leader who is still technically involved, you will mentor and manage data scientists and analysts while having the ability to guide the team through evaluating, selecting, and implementing the right models, paired with an understanding of end to end workflow and ensure the delivery of scalable AI solutions. 

This position requires excellent communication and collaboration skills as you partner closely with internal stakeholders and cross‑functional engineering, product, and clinical teams. In our fast-paced environment, adaptability is key—your ability to reprioritize quickly and lead your team through evolving business needs will ensure maximum impact

What you’ll do:

• Lead, mentor, and develop a high‑performing team of Data Scientists and ML Engineers, ensuring strong execution and continuous skill advancement.
• Contribute to event‑driven architecture design and implementation, enabling asynchronous processing and large‑scale system integration.
• Work seamlessly across functions—partnering with Data Scientists on model tuning, experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies.
• Provide technical leadership in the effective use of AWS services such as Lambda, EC2, EMR, S3, Athena, Batch, Textract, Comprehend, Bedrock.
• Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams.
• Conduct code reviews, provide architectural direction, and champion SDLC best practices, while balancing leadership responsibilities with hands‑on technical contributions to ensure timely, high‑quality delivery.

Required Qualifications:

• 7+ years of overall professional experience delivering data-driven AI/ML-focused solutions. 3+ years of direct team management experience, leading Data Scientists, ML Engineers, or similar technical roles.
• Hands-on experience in Python with strong proficiency in libraries such as Pandas, NumPy, SciPy, Matplotlib, and regular expressions. Advanced SQL querying and optimization for large datasets.
• Practical experience in training, tuning, and testing ML algorithms (e.g., SVM, CART, Bagging, Boosting) and text mining techniques; familiarity with modern ML/DL approaches.
• Experience with prompt engineering and leveraging GenAI for classification, data enrichment, semantic embeddings, and innovative AI-driven solutions.
• Experiment and rapidly prototype design frameworks, validate hypotheses efficiently, and iterate on AI/ML models to support fast-paced development.
• Strong knowledge of Object-Oriented Programming (OOP) and experience creating custom Python packages for serverless applications.
• Hands-on experience with AWS services including Lambda, EC2, EMR, S3, Athena, Batch, Textract, and Comprehend.
• Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems
• Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners.
• Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement.

Good to have:

• Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics.
• Strong thought leadership in AI/ML, including guiding stakeholders on feasibility, risk, architecture, and adoption strategy.
• Prior experience in deploying LLM‑powered production features,optimize prompting strategies, transforming experimental prototypes into robust, scalable services delivered through well‑defined APIs.
• Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing).

Ability to commute/relocate:

• Nacharam, Hyderabad, Telangana*: Reliably commute or planning to relocate before starting work (Preferred)

Interview Process*:

1. Connect with the Hiring Manager for a Preliminary Phone Screening
2. Behavioral Interview(s)
3. Case Study
4. 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 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.

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. 

Opportunity Overview:

We are seeking a Technical, Hands-on Manager to lead a team responsible for building and maintaining high-quality healthcare market datasets and analytics that power internal insights, benchmarking, and external thought leadership.

In this role, you will lead a team of data analysts responsible for the development, quality assurance, and ongoing refresh of market data assets. You will combine strong people leadership with technical expertise in analytics and data science to ensure reliable, scalable data pipelines and actionable insights.

The ideal candidate is both a strong people manager and a hands-on analytics leader who can guide analysts in rigorous data methodology, translate data outputs into meaningful business insights, and partner closely with commercial strategy, product, clinical, and analytics stakeholders.

What you’ll do:

• Lead and develop a team of data analysts responsible for the creation, validation, and ongoing refresh of healthcare market datasets.
• Mentor analysts in data methodology, statistical reasoning, and reproducible analytics practices to ensure consistent and rigorous analysis across the team.
• Establish analytic standards, coding practices, and documentation expectations to ensure all datasets and insights produced by the team are reproducible and scalable.
• Establish and maintain governance processes for market data including versioning, documentation, auditability, and traceability of data sources and methodologies.
• Oversee change-detection logic, ensuring the team systematically identifies and documents additions, removals, and shifts in the market dataset.
• Define and enforce data quality standards across ingestion, transformation, and analysis workflows.
• Collaborate with Data Engineering and Platform teams to ensure the underlying data infrastructure supports scalable ingestion, transformation, and analytics workflows used by the analyst team.
• Translate analytic outputs into business insights, benchmarks, and structured datasets that support product strategy, commercial enablement, and thought leadership initiatives.
• Drive the implementation of project scope definition, effort estimation, and planning in close coordination with cross-functional teams.
• Conduct code reviews and analytics methodology reviews to ensure maintainable, reproducible data workflows and high-quality analytic outputs.

What you’ll need:

Must-haves

• 7+ years of professional experience in data analytics, data science, or quantitative analysis in a production environment.
• Strong proficiency in Python and data analysis libraries (Pandas, NumPy, SciPy, Matplotlib).
• Advanced SQL querying and ability to work with large datasets.
• Strong understanding of statistics, data analysis methods, and pattern detection in complex datasets.
• Experience managing multiple concurrent analytics projects and prioritizing work across a team of analysts.
• Experience designing analytic frameworks or benchmark datasets used by business teams or external stakeholders.
• Experience managing data quality, data governance, and dataset lifecycle management.
• Experience evaluating and applying modern analytics or AI techniques (including LLM-based tools where appropriate) to enrich datasets or accelerate analytic workflows.
• Experiment and rapidly prototype design frameworks and validate hypotheses efficiently.
• Strong software engineering fundamentals including modular Python code, reusable analytic functions, and maintainable data pipelines.
• Familiarity with cloud data platforms (e.g., AWS, GCP, or Azure) and common data services used to store, process, and query large datasets.
• Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering teams to align technical decisions with business goals, ensuring smooth integration of AI/ML capabilities into production systems
• Excellent communication and storytelling skills, capable of translating complex AI/ML concepts into clear, actionable insights for leadership, stakeholders, and non-technical partners.
• Ownership mindset with end‑to‑end accountability, ensuring delivery from concept to deployment to monitoring—while continuously identifying risks, blockers, and opportunities for improvement.

Nice-to-haves

• Background in healthcare payment integrity, clinical data workflows, or payer/provider analytics.
• Thought leadership in analytics-driven market intelligence, benchmarking, or healthcare data insights.
• Experience working with healthcare claims, authorization, or utilization management data.
• Experience producing market intelligence, benchmarking studies, or industry datasets.
• Familiarity with healthcare payer workflows or healthcare analytics environments.
• Familiarity with compliance, governance, and security best practices for healthcare data (HIPAA, PHI handling, logging, auditing).

Ability to commute/relocate:

• Nacharam, Hyderabad, Telangana*: Reliably commute or planning to relocate before starting work (Preferred)

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.

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