Data Scientist Machine Learning Engineer
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Job Location:
Monthly Salary:
Experience Required:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Responsibilities
Build and deploy machine learning models to support business and product decisions.
Develop Python-based data pipelines and ETL workflows.
Work with Azure ML Databricks and cloud-based data platforms.
Use embeddings LLM APIs and vector search techniques when applicable.
Analyze clean and structure large datasets for modeling.
Collaborate with cross-functional teams to define data requirements.
Monitor model performance and retrain as needed.
Support automation and data ingestion (scraping batch pipelines).
Present findings and recommendations to technical and non-technical stakeholders.
Requirements
36 years of experience as a Data Scientist or ML Engineer.
Strong expertise in Python (Pandas NumPy scikit-learn).
Experience with Azure ML Databricks or similar cloud ML platforms.
Solid skills in SQL data modeling and ETL pipelines.
Experience working with embeddings AI APIs (OpenAI Anthropic) or vector databases (preferred).
Ability to deploy and maintain ML models in production.
Familiarity with data scraping and automation tools.
Strong communication and analytical skills.
English B2
Required Skills:
Job Description We are looking for a MidSenior Data Scientist / Machine Learning Engineer to build AI-driven models develop data pipelines and enhance analytical capabilities across the organization. The ideal candidate can create end-to-end ML solutions work with embeddings and AI APIs and deploy models in Azure environments. This role requires a strong analytical mindset fast execution and excellent communication skills. Responsibilities Build and deploy machine learning models to support business and product decisions. Develop Python-based data pipelines and ETL workflows. Work with Azure ML Databricks and cloud-based data platforms. Use embeddings LLM APIs and vector search techniques when applicable. Analyze clean and structure large datasets for modeling. Collaborate with cross-functional teams to define data requirements. Monitor model performance and retrain as needed. Support automation and data ingestion (scraping batch pipelines). Present findings and recommendations to technical and non-technical stakeholders.
Required Education:
Requirements36 years of experience as a Data Scientist or ML expertise in Python (Pandas NumPy scikit-learn).Experience with Azure ML Databricks or similar cloud ML skills in SQL data modeling and ETL working with embeddings AI APIs (OpenAI Anthropic) or vector databases (preferred).Ability to deploy and maintain ML models in with data scraping and automation communication and anal
Company Industry
IT Services and IT Consulting
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
