About Inizio Ignite:

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health.

Company Descriptor

Inizio Ignite is the global advisory partner for health and life sciences, encompassing connected expertise across Research Partnership, Putnam, Vynamic, and STEM. Guided by purpose, passion, and precision, we collaborate with clients to ignite impact, accelerate performance, and deliver lasting change for patients. By uniting strategy, insights, and innovation with a unique depth and breadth of expertise, we drive transformation and shape the future of health. Our Research Partnership healthcare market research team provides research and insights to inform and power healthcare decisions. Serving a variety of clients across the lifecycle, our expertise includes data, research & insights (proprietary syndicated and custom research) and brand tracking (ATU). Proudly part of Inizio – the market-leading commercialization partner for health and life sciences. From early-stage development to loss of exclusivity, we simplify complexity, unlock value, and make collaboration seamless at every pivotal moment – supporting confident, insight-driven decisions that move innovation forward. 

Role Overview

The Data Delivery & Dashboards Executive role will report into the Dashboard Manager. The Data Delivery & Dashboards Executive will be a key member of the newly formed India-based Data Management & Delivery Hub, supporting quantitative healthcare market research projects across global markets. As a Dashboard Developer Executive, you build and maintain high impact dashboards and data visualizations that transform raw market research data into actionable insights. You’ll collaborate with researchers, analysts, and engineers to ensure data flows seamlessly from collections to visual storytelling. You will also support the team in delivering insightful, user-friendly dashboards through automated tools and off-the-shelf solutions. This is a fantastic opportunity to develop your skills in data management, quality assurance, and data visualisation, while working alongside an experienced team in a dynamic, global environment. Skill Set required

What you'll be doing

Brand Equity tracking support with our in-house platform:

• Maintain the pipeline for the project data process flow (this includes receival of data into in-hosue Tool, through the data processing stage into the storage mart, through the python utilities into required outputs)
• Maintain and update python utilities when required due to changes from the research team
• Manage and rectify when failures occur in the pipeline, liaising with both the data providers, research team and developers on the dashboard
• Manage the storage mart and data warehouse
• Support team with edits in-house platform

Data Quality Checks:
Assist in performing detailed quality control checks on large and complex datasets to ensure accuracy, completeness, and consistency.

Data Transformation & Standardisation:
Support the transformation and standardisation of data files to align with internal data structures, project needs, and client-specific formats.

Dashboard Support & Maintenance:
Assist in the creation, population, and maintenance of dashboards using off-the-shelf tools (e.g., Power BI, Tableau, or similar platforms), ensuring outputs are clear, accurate, and aligned with research objectives.

Data Delivery Management:
Help manage and organise the final delivery of data files and dashboards to internal teams and clients, ensuring timely and error-free execution.

Collaboration Across Teams:
Work closely with internal stakeholders including Development team, Data Processing, Scripting, Project Management and Research teams to ensure smooth handovers and integration of deliverables.

Documentation & Reporting:
Maintain clear documentation of processes, data transformation steps, and QC logs to support transparency, reproducibility, and audit-readiness.

Continuous Learning & Development:
Engage in training opportunities to build knowledge in healthcare data, market research workflows, dashboarding tools, and data handling best practices.

What you'll need

Your skills and experience:

Technical Expertise

• Atleast 5+ years expertise in languages like Python and SQL.
• Mastery in advanced Core Python (generators, decorators, OOP, async programming), architecture design.
• Proficient in libraries like Pandas - Joins, Melting, handling missing values, NumPy, TensorFlow etc.
• Proficient in SQL (PostgreSQL, MySQL).
• Understanding MVC/MVT, microservices, and system design principles.
• Experience in setup of data pipelines is highly desirable.
• Knowledge of high-performance framework (Django, FastAPI, Flask) is a plus.
• Cloud platform expertise (AWS, Azure, GCP), and building ETL/ELT pipelines.
• Experience in version control system.

Ideal candidate should be

• You are proactive, dedicated and enthusiastic, with a ‘can do’ attitude and approach
• You demonstrate a high level of accuracy and attention to detail, as well as strengths in organisation and prioritisation
• You are a collaborative team player who works well with colleagues
• You communicate ideas and issues in an effective, straightforward fashion
• Logical thinking and ability to troubleshoot errors or discrepancies in tabulated data.
• Ability to interpret tabulation specifications and apply them accurately.
• Problem-solving skills (particularly relating to situations requiring analytical judgement and establishing best practice solutions)
• You are highly motivated and want to seize opportunities to develop new skills and progress your career

Artificial Intelligence

Inizio may use AI technologies to support certain aspects of our recruitment process, but all hiring decisions are made by our human recruiting team. We are committed to fair, inclusive, and human-led hiring practices. Don't meet every requirement? That's okay! We are dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (10+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.

About the Role

Anaplan is looking for a skilled Python Machine Learning Developer to join our AI engineering organization. This is a crucial, hands-on developer role focused on building the robust backend systems that power our machine learning features. You are not just a developer; you are a software engineer who specializes in bringing ML models to life in a production environment. You will be responsible for designing, building, and deploying the APIs, data pipelines, and backend services necessary to integrate sophisticated machine learning capabilities into the Anaplan platform.

Key Responsibilities

• Design, build, and maintain scalable and reliable machine learning services and APIs using Python.
• Develop and productionize ML models, taking them from prototype to scalable, live systems.
• Construct and manage the data pipelines required for model training, validation, and inference.
• Build and interact with databases (both SQL and NoSQL) to store and retrieve data for ML applications.
• Write clean, high-quality, and well-tested code, adhering to software engineering best practices.
• Collaborate with data scientists, AI architects, and other engineers to integrate ML models into our products.
• Optimize applications for speed, scalability, and reliability.
• Contribute to our MLOps infrastructure to streamline the deployment and monitoring of machine learning models.

Required Qualifications

• Expert (6+ years) Python Programming: Strong, hands-on proficiency in Python for software development.
• Backend & API Development: Proven experience building and deploying backend services and RESTful APIs using frameworks like Flask, FastAPI, or Django.
• Database Proficiency: Solid experience with both SQL (e.g., PostgreSQL) and NoSQL (e.g., MongoDB, Redis) databases, including data modeling and query optimization.
• Machine Learning Libraries: Deep, practical knowledge of the core Python ML ecosystem:
• Data manipulation and analysis: Pandas, NumPy.
• Core ML frameworks: scikit-learn.
• Deep learning frameworks: Experience with TensorFlow or PyTorch.
• Strong understanding of software engineering principles, including data structures, algorithms, and design patterns.
• Experience with version control (Git) and CI/CD practices.
• Excellent problem-solving skills and the ability to write efficient, production-ready code.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms (AWS, Azure, or GCP) and their ML services.
• Familiarity with containerization technologies like Docker and orchestration with Kubernetes.
• Experience with MLOps tools and principles (e.g., MLflow, Kubeflow).
• Knowledge of large-scale data processing frameworks like Spark or Dask.

What Makes This Role Exciting

This role places you at the critical intersection of software engineering and machine learning. You are a builder, responsible for creating the tangible systems that make our AI intelligent. You will tackle complex engineering challenges, from API design to database performance, all within the context of delivering cutting-edge machine learning features. At Anaplan, you will see your code run at scale, directly impacting a product used by leading global enterprises and solving real-world business problems.