Job Responsibilities:

• Data Collection & Cleaning: Gather, preprocess, and clean large datasets from various structured and unstructured sources for AI/ML models.
• Data Analysis & Reporting: Analyze datasets to extract trends, patterns, and insights that contribute to AI/ML model development.
• Collaboration with Data Scientists: Work closely with data scientists and ML engineers to build, evaluate, and optimize machine learning models.
• Feature Engineering: Develop and select relevant features for AI/ML models, ensuring model performance improvement.
• Data Visualization: Create dashboards and visualizations to present key insights and model performance metrics to stakeholders.
• Model Evaluation: Assist in evaluating model accuracy, precision, and recall, and provide suggestions for improvement.
• Automating Processes: Support the automation of data workflows and AI-driven tasks, improving operational efficiency.
• Data Governance: Ensure data accuracy, integrity, and security through best practices in data governance

Required Skills:

• Programming Languages: Proficiency in Python, R, or similar languages used for data analysis.
• Data Manipulation: Expertise in SQL and data manipulation tools (Pandas, NumPy, etc.).
• Machine Learning Frameworks: Familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Data Visualization Tools: Experience with BI tools such as Tableau, Power BI, or Matplotlib.
• Database Management: Knowledge of relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra).
• AI/ML Knowledge: Understanding of machine learning algorithms, natural language processing, and AI techniques.
• Strong Analytical Mindset: Ability to approach problems with a structured and analytical mindset to provide actionable insights.