BD&I ML Engineer

Must have skills:

Python azure data factory Databricks Apache Spark / PySpark Azure Data Lake Store Azure Data Lake Analytics Pipeline Execution/ETL Machine Learning AI ETL clould data pipelines Docker Kubernetes AWS

About the Role
We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities
Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.Conduct exploratory data analysis and feature engineering to improve model performance.Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.Monitor and optimize the performance of deployed models in production.Stay up-to-date with the latest advancements in machine learning and related technologies.Collaborate with cross-functional teams to integrate machine learning solutions into existing systemsCommunicate technical concepts and findings to both technical and non-technical audiences.Stay abreast of the latest advancements in data science and machine learning techniques.Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:
2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.Excellent problem-solving and analytical skills.Communication and collaboration skills.Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.3+ years of experience in developing and deploying machine learning models in a professional setting.Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Excellent problem-solving and analytical skills.Strong communication and collaboration skills. Soft Skills:Strong problem-solving and critical thinking skillsAbility to break down complex technical topics for business stakeholdersComfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:
Bachelor's degree in Computer Science or related field.Master’s degree or equivalent advanced degree preferred.Proven track record of delivering data science projects from ideation to production.Strong communication skills and the ability to tell compelling stories with data.Comfortable with both structured and unstructured data sets.

About the Role
We are seeking a talented and passionate Machine Learning Engineer to join our growing team. In this role, you will be responsible for developing and implementing machine learning models to solve real-world problems and drive business value. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy innovative solutions.

Key Responsibilities
Design, develop, and implement machine learning models for various applications, such as predictions, customer churn analysis, and fraud detection.Collect, clean, and preprocess large datasets for training and evaluation.Conduct exploratory data analysis and feature engineering to improve model performance.Evaluate and select appropriate machine learning algorithms and techniques based on business requirements and data characteristics.Develop and maintain machine learning pipelines for data ingestion, preprocessing, training, and deployment.Monitor and optimize the performance of deployed models in production.Stay up-to-date with the latest advancements in machine learning and related technologies.Collaborate with cross-functional teams to integrate machine learning solutions into existing systemsCommunicate technical concepts and findings to both technical and non-technical audiences.Stay abreast of the latest advancements in data science and machine learning techniques.Mentor and guide junior data scientists, fostering a collaborative and knowledge-sharing environment.

What You Bring

Experience:
2 to 3 years of experience in developing and deploying machine learning models in a professional setting.

Telecom industry experience is highly preferred.

Technical Skills:
Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Building & deploying model using python Azure Data Factory (ADF), Azure Databricks, PySpark, Delta Lake, ETL/ELT, data pipelines, data lakehouse architecture.Excellent problem-solving and analytical skills.Communication and collaboration skills.Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.3+ years of experience in developing and deploying machine learning models in a professional setting.Strong understanding of machine learning algorithms and techniques, including supervised, unsupervised, and reinforcement learning.Proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).Excellent problem-solving and analytical skills.Strong communication and collaboration skills. Soft Skills:Strong problem-solving and critical thinking skillsAbility to break down complex technical topics for business stakeholdersComfortable working in a fast-paced, agile environment with shifting priorities

Qualifications:
Bachelor's degree in Computer Science or related field.Master’s degree or equivalent advanced degree preferred.Proven track record of delivering data science projects from ideation to production.Strong communication skills and the ability to tell compelling stories with data.Comfortable with both structured and unstructured data sets.

Exciting Projects:

Collaborative Environment:

Work-Life Balance:

Professional Development:

Excellent Benefits:

Fun Perks: