Doceree - Data Scientist - Machine Learning

Description

About Doceree :

Doceree is a growing AdTech organisation delivering innovative solutions.

As the first global network of physician-only platforms for programmatic messaging, Doceree is transforming the digital communication landscape in the global healthcare industry.

Doceree provides the most comprehensive solution to Healthcare and Lifesciences advertisers to reach the target audience in the most effective and efficient way through programmatic digital advertising.

Our Core Belief

Technology can connect the fragmented healthcare ecosystem to deliver information when it is most needed to improve patients' outcomes.

We are expanding our footprints across the globe and enhancing our services, offering, and developing new products and solutions to address the unmet needs of industry.

Doceree is operating in 25+ countries currently with offices in NY, India and London.

Position Title : Data Scientist

Department : Product & Engineering.

Location : Noida, India.

Work Setting : Onsite.

Purpose Of The Job

Doceree, the global leader in physician-level data-driven marketing and messaging, is looking for a highly skilled Data Scientist who is passionate about solving real-world business problems using machine learning.

This role focuses on designing and implementing advanced ML models at the intersection of healthcare and programmatic advertising to drive measurable impact on revenue and marketing effectiveness.

You'll work on business-critical use cases that improve targeting, messaging performance, personalization, and decision-making across the platform.

A strong background in analyzing complex data, detecting anomalies, engineering relevant features, identifying clusters, and building scalable ML prototypes is essential.

This is an ideal opportunity for someone who thrives at the intersection of data, algorithms, and business strategy, and wants to help build next-generation AI/ML capabilities in healthcare marketing.

Key Responsibilities

• Design, train, and deploy a variety of high-impact machine learning modelsincluding classification, look-alike modeling, recommendation engines, uplift modeling, ranking algorithms, sequence models (RNNs, LSTMs), transformers, CNNs, and graph-based modelsto address key business problems such as physician segmentation, personalized targeting, next-best-action prediction, churn prediction, audience expansion, anomaly detection, and engagement scoring.
• Prototype multiple modeling approaches and iterate quickly to determine the best performing models before scaling them on large datasets.
• Collaborate with cross-functional product and engineering teams to understand business goals and translate them into ML-based solutions with measurable impact.
• Analyze large and complex datasets to uncover patterns, trends, data quality issues, and key drivers influencing model outcomes.
• Select meaningful features, assign appropriate weightages, and validate their business relevance for high-impact ML solutions.
• Build and optimize scalable data and model pipelines using cloud platforms (AWS, Databricks) and modern MLOps tools.
• Utilize ML/DL libraries and frameworks such as scikit-learn, TensorFlow, Keras, PyTorch, SpaCy, NumPy, and Pandas to build production-ready models.
• Continuously evaluate model performance, retrain as necessary, and stay current with advancements in NLP, recommendation systems, transformers, and other relevant areas.
• Support the integration of ML models into production environments in collaboration with the engineering team.
  
  

Qualifications Requirement : Skills & Education :

• 2 - 8 years of experience building and deploying machine learning solutions in real-world settings, preferably with measurable business or revenue impact.
• Proven experience with a range of ML techniques, including classification, clustering, recommendation engines, time series forecasting, and deep learning architectures like CNNs, RNNs, and Transformers.
• Strong expertise in Python, SQL, and ML/DL libraries (e.g., TensorFlow, Keras, PyTorch, scikit-learn, SpaCy, NumPy).
• Demonstrated ability to analyze noisy, incomplete, or biased data to identify anomalies, segment users, and engineer high-value features.
• Forecasting of different trends like campaign spends, reach and publisher earnings as value driven business use cases.
• Hands-on experience with cloud services (AWS, Databricks) and MLOps tools for model lifecycle management.
• Strong problem-solving and solution-oriented mindset with the ability to test and compare multiple modeling strategies quickly.
• Comfortable working with large-scale datasets and building end-to-end ML pipelines.
• Excellent communication skills and ability to explain complex ML concepts to non-technical stakeholders.
  
  

Preferred Qualifications

• Understanding of mathematical principles behind ML algorithms, including linear algebra, calculus, probability, and statistics.
• Understanding of GenAI applications in marketing and personalization.
• Experience with healthcare or digital marketing domains, especially in programmatic advertising.
• Familiarity with containerization (Docker, Kubernetes) and big data tools (Spark, Aerospike etc).
  
  

Why Explore a Career At Doceree

• Be a Part of the Revolution in Healthcare Marketing.
• Innovate with Us to Unite and Transform the Healthcare Providers (HCPs) Ecosystem for Improved Patient Outcomes.
• Doceree has been recognized and certified two times in a row Best places to work NJ 2023, Great Place to work 2023.
• Below are the competitive benefits which will be provided to the selected candidates basis their location.
• If you are passionate about health technology and have a knack for turning complex concepts into compelling narratives, we invite you to apply for this exciting opportunity to contribute to the success of our innovative health tech company.
  
  

Doceree Benefits

Below are the competitive benefits that will be provided to the selected candidates basis their location.

• Competitive Salary Package.
• Generous Leave Policy.
• Flexible Working Hours.
• Performance-Based Bonuses.
• Health Care Benefits.
  
  

(ref:hirist.tech)