Req ID 73498 | Hyderabad, India, ZF India Pvt. Ltd.

  

Job Description

Translating business requirements into Data Science solutions leveraging strong business acumen. Applying technical knowledge to architect solutions that meet business needs and align with AI/AA roadmaps. Contributing to scalable architectures that support additional modeling use cases (e.g., Azure ML, Azure Data Lake, Azure Databricks, Azure Data Factory, Azure Synapse Analytics, Azure SQL, Azure EventHub/IoT Hub, etc.). Designing machine learning pipelines that curate datasets, train, test, and validate models. Comparing model performance to existing or previously catalogued models, packaging models, and deploying them for real-time serving or batch scoring activities. Conducting data profiling, cataloging, and data mapping for technical design using a use case-based approach that drives the construction of technical data flows. Working with various data sources, including data lakes, data warehouses, NoSQL databases, and APIs. Implementing ETL processes to ensure data accessibility and integrity. Setting up data and experimental platforms. Collaborating with stakeholders to understand needs and align AI initiatives with business objectives. Leading and mentoring a team of AI engineers and data scientists. Excellent communication skills to listen, understand questions, and deliver clear insights. Outstanding team player with the ability to work collaboratively in a multidisciplinary environment.

Education

Bachelor's or Master's degree in Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.

Skills Required

At least three years of hands-on experience with data science, AI, and big data; experience with data engineering is a plus. Deep understanding of statistical and machine learning modeling with experience applying these techniques to business problems. Proficiency in machine learning algorithms such as k-NN, Naive Bayes, decision trees, SVM. Experience using data mining and statistical tools. Solid pattern recognition and predictive modeling skills. Knowledge of recommendation engines, scoring systems, and A/B testing. Experience leveraging a variety of services as data sources, such as Azure Data Lake, Azure Synapse Analytics, Azure SQL. Hands-on experience with analytics and big data technologies within Microsoft Azure, including tools like Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Synapse Analytics. Knowledge and experience with distributed techniques for training and scoring machine learning models, ideally using Azure Databricks. Proficiency with one or more cloud-available machine learning frameworks and tools such as TensorFlow, PyTorch, ONNX, NumPy. Experience with model management, ideally using Azure ML service and/or MLFlow, and deployment of models using Azure Kubernetes Service. Knowledge of using automated machine learning (AutoML) frameworks to enhance productivity. Experience working with Python, Scala, and/or T-SQL. Extensive experience connecting to data platforms including data lakes, data warehouses, NoSQL databases, and APIs. Ability to set up data and experimental platforms. Strong analytical skills with attention to detail. Self-organized with the ability to estimate, prioritize, and schedule tasks effectively. Motivation and commitment to get involved, learn, and contribute to the development of leading-edge technologies. Fluent in English; proficiency in German is an advantage.

 

 

Be part of our ZF team as Senior Engineer and apply now!

Contact

Sharifunnisa Mohammed