EchoGlobal

Although the role is focused on data migration, it is not in the traditional analytics or data science sense. The work involves migrating customer data into an application rather than into a data lake or data warehouse for analytical use. This won't be boring. One month you will be migrating data from Software A, the next from Software B and after that from a custom-built legacy app C, each with its own challenges and trade-offs.

We do understand that very few engineers specialize solely in migrations. So, if you are a software engineer, DB developer or DevOps professional with relevant migration experience, this is a great opportunity to join a serious product used by thousands of companies worldwide and make a real impact.

Requirements

• 2+ years of experience in data migrations.
• Proficiency in SQL.
• Hands-on experience with scripting in Python or Ruby (as popular ETL tools are not widely used in this role).
• Ability to take ownership of tasks with minimal direction and deliver high-quality results in a fast-paced environment.
• Self-starter who can work independently and collaboratively.
• Excellent communication, analytical, and problem-solving skills.
• Advanced level of English.

Responsibilities

• Work with data owners to understand legacy data, gather requirements, and design solutions to meet those needs.
• Produce detailed data mapping documentation.
• Develop and implement tools, scripts, queries, or applications for accessing, analyzing, converting, and migrating data between databases or from CSV files.
• Reverse-engineer data models from other vendors.
• Troubleshoot data quality issues and write scripts to cleanse data.
• Maintain data security, integrity, and availability in production environments.
• Collaborate with the Customer Success team to manage client expectations, communicate timelines, and resolve database issues.
• Serve as the technical point of contact during the migration process.

Nice to have

• Linux experience, including terminal usage and OS-level troubleshooting.
• Bachelor’s degree in Computer Information Systems or a related field.

Working conditions

• Mon — Fri, 8h/day, overlap with EST (US) at least 6 hours.

Interviewing stages

1. In-depth HR interview assessing your soft skills, English proficiency, etc.
2. Interview with CTO (chat + live coding test).
3. Final meet with your team lead (chat + live coding test).

About the Role

We are seeking a highly skilled and mission-driven Data Scientist to join our customer team and lead the development of our Patient Risk Scoring machine learning initiatives. In this role, you will build predictive models that identify high-risk patients for interventions, ultimately improving patient outcomes and optimizing care delivery. You will leverage Microsoft Fabric to manage end-to-end machine learning workflows, drawing insights from Electronic Health Record (EHR) data sources. If you are passionate about the intersection of advanced artificial intelligence and healthcare innovation, we want to hear you.

Responsibilities

• Model Development & Deployment: Design, train, evaluate, and deploy machine learning models to predict patient risk scores (e.g., medication refusal, non-compliance, decompensation etc.).
• EHR Data Engineering & Processing: Extract, clean, and transform healthcare data from EHR systems (e.g., Credible) to build robust feature sets for predictive modeling.
• End-to-End Analytics with Microsoft Fabric: Utilize Microsoft Fabric’s unified analytics platform (including Data Engineering, Data Science, and Real-Time Analytics workloads) to orchestrate data pipelines, manage Lakehouse architectures, and scale ML training/inference.
• Clinical Collaboration: Partner closely with clinical stakeholders, medical officers, and care teams to define risk cohorts, ensure the clinical validity of model features, and translate model outputs into actionable clinical workflows.
• MLOps & Monitoring: Establish continuous integration, deployment, and monitoring of ML models to track data drift, model degradation, and fairness/bias over time.
• Compliance & Privacy: Ensure all data handling and modeling practices strictly adhere to healthcare regulations (e.g., HIPAA, HITRUST) and maintain the highest standards of data security and patient privacy.

Qualifications

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Bioinformatics, Health Informatics, or a related quantitative field.
• Professional Experience: 4+ years of experience developing and deploying machine learning solutions in production environments, preferably within healthcare or clinical data ecosystems.
• Microsoft Fabric Experience: Hands-on experience building and deploying data and ML workflows within the Microsoft Fabric ecosystem (OneLake, Notebooks, Spark, Data Factory).
• Machine Learning Proficiency: Strong grasp of classical machine learning algorithms (e.g., XGBoost, Random Forests, Logistic Regression) and modern deep learning techniques, specifically for tabular and time-series data.
• Programming Skills: Advanced proficiency in Python and SQL. Experience with data manipulation and ML libraries (Pandas, PySpark, Scikit-Learn, PyTorch, or TensorFlow).
• Communication: Excellent ability to translate complex technical and statistical concepts to non-technical clinical and business stakeholders.

Nice to Have

• Cloud Certifications: Relevant Microsoft Azure or Fabric certifications.

Work Environment & Collaboration

• Full-time: 8 hours a day.
• Schedule: Mon – Fri 9-5 (US EST) overlap with team at least 4 hours.
• Team Structure: Work independently on assigned tasks with support from experienced team members.
• Communication: Primarily asynchronous via email and MS Teams.