Key skills
AWSAzureCloudGoogle Cloud PlatformHadoopPythonPyTorchScikit-LearnSparkSQLTableauTensorflowRAIMachine LearningMLDeep LearningNLPNatural Language ProcessingComputer VisionTensorFlowscikit-learnAnalyticsBIPower BIGCPGoogle CloudCommunicationPresentation Skills
About this role
Role Overview
- Collect, clean, and preprocess large volumes of structured and unstructured data from multiple sources.
- Develop and maintain data pipelines to ensure the accurate and efficient processing of data.
- Handle data inconsistencies, missing values, and outliers, ensuring high-quality, usable datasets for analysis.
- Perform detailed exploratory data analysis (EDA) to understand data patterns, trends, and relationships.
- Visualize data using tools such as Tableau or Power BI to identify key insights and drive decision-making.
- Apply AI and machine learning algorithms (e.g., classification, regression, clustering, deep learning) to build predictive and prescriptive models.
- Train, tune, and evaluate machine learning models to optimize their performance.
- Automate model deployment and update processes for continuous improvement in accuracy and efficiency.
- Use statistical methods and machine learning techniques to forecast trends, identify anomalies, and detect patterns in large data sets.
- Apply natural language processing (NLP) and computer vision techniques for text and image data analysis when needed.
- Communicate findings clearly through visualizations and reports to stakeholders across the organization.
- Present complex data insights in an accessible and actionable format for both technical and non-technical audiences.
- Work closely with cross-functional teams to understand business needs and objectives.
- Provide analytical support to business stakeholders by offering data-driven insights and recommendations.
- Stay updated on the latest trends in AI/ML technologies and data analytics.
Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a quantitative related field.
- 2-5 years of experience in data analysis, data science, or machine learning roles, with hands-on experience in managing and analyzing large datasets.
- Proficiency in Python, R, or similar programming languages for data analysis and machine learning.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Familiarity with AI techniques, including deep learning, reinforcement learning, and NLP.
- Strong knowledge of SQL for querying large data sets.
- Expertise in data visualization tools (e.g., Tableau, Power BI).
- Experience with big data platforms and tools (e.g., Hadoop, Spark) is a plus.
- Familiarity with cloud platforms (AWS, GCP, Azure) for data storage and processing.
- Strong problem-solving and critical-thinking abilities.
- Excellent communication and presentation skills.
- Ability to work independently and as part of a team.
- Attention to detail and the ability to work with complex data sets.
- Experience with deploying machine learning models to production environments is preferred.
- Knowledge of advanced analytics techniques such as time series forecasting, anomaly detection, or reinforcement learning is preferred.
- Experience in a real estate industry is a plus.
Tech Stack
- AWS
- Azure
- Cloud
- Google Cloud Platform
- Hadoop
- Python
- PyTorch
- Scikit-Learn
- Spark
- SQL
- Tableau
- Tensorflow
Benefits
- A competitive and comprehensive benefits package.