Data Scientist (Healthcare AI)

Job Description

Title: Data Scientist (Healthcare AI)

Company Name: Labaid AI Ltd.

Vacancy: 2

Age: At least 20 years

Job Location: Dhaka

Salary: Negotiable

Experience:

Published: 2026-07-19

Application Deadline: 2026-07-31

Education:

Requirements:

Skills Required:

Additional Requirements:

• Age At least 20 years

Data Scientist (Healthcare AI)

Company:

Labaid AI (a Labaid Group company)

Position:

Data Scientist — Healthcare Intelligence

Vacancy:

01

Job Location:

Dhaka (Labaid AI office; occasional visits to Labaid hospital and diagnostic sites)

Employment Status:

Full-time

Salary:

Negotiable

About Labaid AI

Labaid AI is building trusted vertical AI for healthcare, identity, and edge intelligence in Bangladesh. Backed by Labaid Group — one of the country's largest private healthcare brands with ~3 million annual patient encounters, ~1,000 consultant physicians, and a nationwide diagnostics network — we build AI products that run inside real clinical and operational workflows: LUNA (agentic healthcare assistant platform), MedPAC (AI-assisted enterprise imaging/PACS), MyHealth (oncology-first clinical copilot), Digital RM (AI relationship manager), and FLVE / Edge Vision (identity and edge AI appliances).

This is a rare role in Bangladesh: you will work with real, high-volume clinical, imaging, and operational data that almost no other local data science team can access.

Job Context

We are hiring a Data Scientist to turn Labaid's clinical and operational data into models, insights, and evaluation systems that power our products. You will sit at the centre of the product loop: framing problems with clinicians and product leads, building datasets, training and validating models, and measuring whether our AI actually works — safely — in production.

Job Responsibilities

·        Design, build, and validate predictive and analytical models on healthcare data: patient flow and demand forecasting, no-show/follow-up adherence prediction, triage and risk scoring, oncology journey analytics, diagnostic TAT and operational optimization.

·        Build and curate high-quality datasets from hospital systems (HMS/EHR, LIS/RIS, PACS metadata, call-centre and RM logs), including cleaning, de-identification, labeling strategy, and dataset documentation.

·        Develop and run evaluation harnesses for LLM and agentic products (LUNA, MyHealth, Digital RM): grounding/faithfulness checks, Bangla/Banglish/English response quality, safety and escalation behaviour, regression suites for prompt and model changes.

·        Support the medical imaging team with statistical validation of vision models (classification/detection/segmentation): sensitivity/specificity, ROC/AUC, reader-study design, drift monitoring.

·        Run experiments and A/B tests; quantify business and clinical impact (missed-revenue recovery, follow-up rates, report turnaround, triage accuracy) and present findings to technical and non-technical stakeholders including clinicians.

·        Contribute to Bangla-language data assets: corpus building, annotation guidelines, quality control for Bangla/Banglish medical text and speech data.

·        Work with engineers to move models from notebook to production, and define the monitoring metrics that keep them honest after deployment.

·        Uphold data governance: consent, minimization, de-identification, and auditability in every dataset and model you touch.

Educational Requirements

·        B.Sc. in Computer Science & Engineering, Statistics, Applied Mathematics, or a related quantitative field from a reputed university.

·        M.Sc./research experience is a plus, especially in ML, biostatistics, or health informatics.

·        Strong portfolios (publications, Kaggle, open-source, deployed projects) are weighted alongside formal degrees.

Experience Requirements

·        1–3 years in data science, applied ML, or analytics roles (exceptional candidates outside this band will be considered).

·        Prior exposure to healthcare, insurance, fintech, or other regulated/high-stakes data environments is a strong plus.

Additional Requirements (Skills)

Must have:

·        Strong Python (pandas, NumPy, scikit-learn) and strong SQL.

·        Solid statistics: hypothesis testing, experiment design, calibration, handling imbalanced and messy real-world data.

·        Experience with at least one deep learning framework (PyTorch preferred; TensorFlow acceptable).

·        Ability to communicate findings clearly in English; working proficiency in Bangla (our users and much of our data are Bangla-first).

Nice to have:

·        LLM evaluation experience (RAG evaluation, hallucination/grounding metrics, human-eval design).

·        Bangla NLP experience (tokenization, embeddings, ASR/OCR data, annotation workflows).

·        Medical imaging or DICOM exposure; familiarity with clinical terminology or FHIR.

·        Vector databases (pgvector, Qdrant, FAISS), MLflow or similar experiment tracking, Docker.

·        Dashboarding (Metabase/Superset/Power BI) for stakeholder-facing analytics.

Other:

·        Both males and females are encouraged to apply.

·        No age limit — we hire for capability.

What You Get

·        Competitive salary, reviewed yearly.

·        2 festival bonuses per year (as per company policy).

·        Medical coverage through the Labaid healthcare network.

·        Mobile allowance.

·        Weekly holiday: Friday.

·        Dedicated GPU/compute resources and access to clinical datasets unavailable anywhere else in Bangladesh.

·        Training budget and direct mentorship exposure to clinicians, radiologists, and the founding engineering team.

·        The chance to ship AI that measurably improves cancer care, diagnostics, and patient experience for millions of Bangladeshis.

Interview Format — Come Prepared to Showcase Your Work

·        Project showcase (mandatory): Present your own work covering both data science and pipelines — the modeling/analysis side (problem framing, features, model choice, evaluation, results) and the engineering side (how the data flowed, how the model was trained, deployed, or would reach production). Bring your laptop with code, notebooks, or a live demo. Slides alone are not enough — we will ask to see the work.

·        Technical deep-dive Q&A: Expect detailed questions on your projects and on fundamentals — statistics, ML theory, evaluation metrics, data handling, and how you'd take a model from notebook to production. Be ready to defend every decision: why this model, why this metric, what failed, what you'd do differently.

·        We are assessing understanding, not memorization. Candidates who can clearly explain the why behind their work will stand out over those with impressive-sounding but shallow project lists.

How to Apply

Email your CV (PDF) to hr@labaidcancer.com with subject line: Data Scientist – [Your Name].

Include links to anything you've built: GitHub, publications, Kaggle, deployed products. A short note on the most interesting dataset problem you've solved beats a cover letter.

Labaid AI is an equal-opportunity employer. All clinical data work follows strict consent, de-identification, and audit policies; AI supports clinicians — doctors diagnose and prescribe.