Junior Data Scientist

Role Snapshot

Company

DenuoSource

Location

Hyderabad (Hybrid)

Department

Data Science & Analytics

Employment Type

Full-Time

Company

DenuoSource

About the Team

DenuoSource has been building healthcare technology since 2007, and we're still a lean team by choice. That means your work doesn't disappear into a big org chart, it shows up directly in decisions that affect patient care. DenuoSource is committed to building an inclusive workplace where people of all backgrounds, identities, and experiences can do their best work and grow their careers. We welcome applicants from all walks of life and evaluate every candidate on the strength of what they can bring to our mission.

You'll join our Data Science & Analytics team at DenuoSource, a hands-on group of data scientists, ML engineers, and analysts working directly with clinical operations, product, and research.

The Opportunity

We are looking for a Junior Data Scientist to join our healthcare data science team. Someone equally comfortable digging into a messy EHR dataset, standing up a first-pass predictive model, and explaining what it means to a room of clinicians. This is a broad, hands-on role. You will move between business analytics, applied ML, and clinical and research data work, with real exposure to production ML systems and modern MLOps practices from day one.

If you like learning fast, owning outcomes early, and working somewhere your models enhance patient care, this is built for you.

What You'll Do

●       Partner with healthcare operations, clinical, and product stakeholders to turn open-ended questions into structured analyses, building dashboards and reports that drive real decisions

●       Support the full ML development lifecycle: data collection, cleaning, feature engineering, model training, evaluation, and handoff to production

●       Contribute to predictive and risk models across use cases like patient risk stratification, care gap identification, readmission prediction, and operational forecasting

●       Work with clinical and research data, including structured EHR data, claims, and other healthcare datasets, with a sharp eye for data quality, privacy, and compliance (HIPAA and PHI handling)

●       Write clean, well-documented SQL (PostgreSQL) to query, join, and shape large relational datasets

●       Collaborate with data engineers and ML engineers on data pipelines, model deployment, and monitoring, getting hands-on exposure to real MLOps workflows: versioning, experiment tracking, and CI/CD for ML

●       Explore applications of generative AI and foundation models where they can meaningfully improve workflows, such as clinical text summarization, information extraction, or decision support

●       Communicate findings clearly through visualizations, reports, and presentations to both technical and non-technical or clinical audiences

●       Keep growing: this role is designed to develop you into a mid-level data scientist within 12 to 18 months

What You'll Bring

●       Bachelor's/ Master's degree in data science, Statistics, Computer Science, Biostatistics, Bioinformatics, or a related quantitative field

●       0 to 2 years of experience in a data science, analytics, or ML-adjacent role. Recent graduates are welcome to apply

●       Solid grounding in machine learning and predictive modelling, statistics, probability, and experimental design

●       Proficiency in Python for data analysis and modelling (pandas, NumPy, scikit-learn)

●       Working knowledge of SQL, with PostgreSQL experience a strong plus

●       Understanding of the end-to-end ML lifecycle, from raw data to a shipped, monitored model

●       Foundational knowledge of MLOps concepts: version control (Git), experiment tracking, model deployment, and monitoring

●       Basic hands-on exposure to a cloud platform (AWS) for storage, compute, or ML services

●       Sharp analytical instincts, comfortable with ambiguity and turning a vague ask into a clear analytical plan

●       Strong communication skills, able to translate technical findings into language clinicians and business stakeholders use

Nice to Have (Bonus Points)

●       Hands-on experience with generative AI and foundation or foundry models (for example, Azure AI Foundry, AWS Bedrock, or similar model catalogs): prompt engineering, fine-tuning, or RAG pipelines

●       Exposure to neural networks and deep learning frameworks (TensorFlow, PyTorch, or Keras)

●       Familiarity with healthcare data standards and interoperability: HL7, FHIR, ICD-10/CPT coding, EHR/EMR systems

●       Experience with containerization (Docker) and workflow orchestration (Airflow or similar)

●       Exposure to experiment tracking and model registry tools (MLflow, Weights & Biases)

●       Understanding of responsible AI principles: fairness, explainability, and bias mitigation, especially relevant in a clinical context

Tools & Tech, You'll Work With

Languages: Python, SQL

Databases: PostgreSQL

ML/DS: scikit-learn, pandas, NumPy, TensorFlow or PyTorch

MLOps: Git, MLflow or model registry or W&B

Cloud: AWS

Visualization/BI: Power BI, or Dash

Gen AI: Foundry models, AWS Bedrock, Coding Agents

What Success Looks Like in Your First 6 Months

●       You have shipped your analysis or dashboard that directly informed a business or clinical decisions

●       You have contributed meaningfully to at least three model, from feature engineering through evaluation

●       You are comfortable navigating our data infrastructure, from raw source through PostgreSQL to production

●       You have picked up our MLOps workflow and can independently version, track, and monitor experiments

●       You have built real working relationships with data engineering, ML engineering, and clinical or business stakeholders

Benefits & Perks

·      Comprehensive health insurance and wellness support

·      Generous PTO and flexible time off

·      Annual learning and professional development stipend

·      Hybrid work setup based out of our Hyderabad office