Position:
Machine Learning Scientist
Company:
DP World
Location:
Bengaluru, Karnataka, India
Job Type:
Full-Time
Job Mode:
On-site
Job Requisition ID:
Not specified
Years of Experience:
Not explicitly mentioned (fresh graduates within the last 12 months or upcoming graduates are eligible)
Company Description:
DP World is a global leader in logistics, supply chain, and trade facilitation, with a strong presence across the globe.
The company’s mission revolves around making global trade more efficient, sustainable, and customer-focused by leveraging innovation and advanced technologies.
Operating in over 60 countries with a workforce of more than 10,000 employees, DP World connects markets and delivers integrated trade solutions.
DP World strives to drive economic growth and improve lives by enhancing the efficiency of trade flows.
The organization has a robust commitment to sustainability, aiming to minimize its environmental impact and invest in local communities.
Profile Overview:
As a Machine Learning Scientist at DP World, you will be a key contributor to developing and deploying machine learning models to drive business insights and optimize operations.
The role involves close collaboration with cross-functional teams such as data scientists, software engineers, and product managers to identify and solve complex ML problems.
You will be responsible for designing algorithms, preprocessing large datasets, training models, and ensuring scalability and performance.
The ideal candidate will have a strong foundation in machine learning concepts, proficiency in Python, and experience with ML frameworks like TensorFlow and PyTorch.
You will play a vital role in ensuring the reliability and robustness of models in production environments using cloud platforms and MLOps best practices.
This position offers opportunities to showcase your ML expertise, work on cutting-edge projects, and contribute to the company’s data-driven decision-making.
Key Accountabilities:
Collaboration:
Work closely with cross-functional teams to define machine learning problems and set clear objectives.
Partner with stakeholders to understand business challenges and translate them into ML solutions.
Model Development:
Research, design, and implement various machine learning algorithms, including supervised, unsupervised, deep learning, and reinforcement learning techniques.
Analyze and preprocess large-scale datasets for training and evaluation purposes.
Model Training and Optimization:
Train and test machine learning models while ensuring accuracy, scalability, and performance.
Optimize models to meet business and technical requirements.
Deployment:
Deploy machine learning models into production environments using cloud platforms such as AWS, Azure, or GCP.
Apply MLOps best practices to ensure smooth deployment and maintenance.
Monitoring:
Continuously monitor and evaluate the performance of deployed models to maintain reliability and robustness.
Identify areas for improvement and implement necessary adjustments to enhance model performance.
Documentation:
Document methodologies, results, and findings to provide insights to stakeholders.
Maintain clear and comprehensive documentation for reproducibility and knowledge sharing.
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
Strong proficiency in Python or a similar programming language.
Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of linear algebra, probability, statistics, and optimization techniques.
Familiarity with key machine learning algorithms, including decision trees, SVMs, and neural networks.
Knowledge of concepts such as feature engineering, overfitting, and regularization.
Hands-on experience with structured and unstructured data using tools like Pandas, SQL, or Spark.
Strong critical thinking skills and the ability to apply theoretical knowledge to solve complex ML problems.
Excellent communication and collaboration skills for effective teamwork.
Additional Skills (Good to Have):
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Knowledge of MLOps tools like MLflow and Kubeflow.
Familiarity with distributed computing or big data technologies, such as Hadoop and Apache Spark.
Previous experience through internships, academic research, or projects demonstrating ML expertise.
Proficiency in deployment frameworks like Docker and Kubernetes.
Additional Info:
The role offers exposure to cutting-edge technologies and innovative projects that align with global trade and logistics.
DP World fosters a collaborative and inclusive work environment, encouraging employees to bring fresh perspectives and ideas.
You will have opportunities to learn and grow within a dynamic team of industry experts.
The company values continuous learning and professional development, providing access to training programs and resources.
As a Machine Learning Scientist, you will directly contribute to optimizing global trade processes and enhancing supply chain efficiency.
Please click here to apply.
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