Sr. Machine Learning Data Scientist

Job Description (Job Summary/Roles & Responsibilities)

'Role Description

We are seeking a highly skilled and experienced Senior Data Scientist to join our team. In this role, you will be at the forefront of applying data science and machine learning techniques to address complex business challenges and drive innovation. With a minimum of 10 years of professional experience as a data scientist, you will leverage your expertise to design, develop, and implement sophisticated models for regression, predictions, ranking, and trend analysis.

Your primary responsibility will be to create data-driven solutions by exploring large and complex datasets, engineering features to enhance model performance, and deploying robust machine learning systems.

The role emphasizes hands-on technical work and requires a solid understanding of big data ecosystems and scalability challenges. Experience with Azure Machine Learning is a significant advantage, as the organization actively utilizes cloud-based tools for model development, deployment, and monitoring.

In addition to technical expertise, you will bring a strategic mindset to ensure that data-driven insights align with and advance organizational goals.

Key Responsibilities

• Selecting features, building, and optimizing classifiers using machine learning techniques
• Hypothesis testing, being able to develop hypothesis and test them with careful experiments
• Experience in implementing Predictive modelling
• Collaborate with cross-functional teams (data engineers, front-end developers, security specialists) to integrate AI models into business solutions.
• Conducts research and experiments to improve AI models and algorithms. Stays updated with the latest AI/ML technologies and trends.
• Implements and deploys AI models using cloud AI services.
• Ensures the quality and scalability of AI solutions

Requirements

• At least 10 years- experience in Predictive Analytics and Data Mining with hands-on experience in the following areas
• Linear Regression
• Classification Techniques
• Logistic Regression
• Discriminant Analysis
• Unsupervised Learning techniques like k-means/hierarchical clustering
• Feature reduction methods like PCA, SVD
• Experience in Optimization methods
• Experience with working in R/Python, T-SQL etc, and graph-based models
• Must have hands on development experience with Python
• Proven experience as a Data Scientist and machine learning model builder
• Understanding of Azure Machine Learning and other Azure AI tools. Proficiency in data modelling and design, including SQL development
• Develop and deploy machine learning models for key use cases, including regression, predictive analytics, ranking systems, and trend forecasting. Hands-on implementing various machine learning algorithms such as linear regression, deep learning using neural networks, logistic regression, decision trees, and clustering algorithms.
• Perform advanced feature engineering to optimize models and extract meaningful patterns from raw data.
• Work with large-scale datasets, ensuring efficiency and scalability in data processing and analysis
• Collaborate with stakeholders to understand business challenges and design data science solutions that meet organizational needs.
• Strong understanding of statistical analysis and machine learning algorithms.
• Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.
• Present analytical findings and business insights to project managers, stakeholders, and senior leadership and keep abreast of new statistical / machine learning techniques and implement them as appropriate to improve predictive performance.
• Excellent problem-solving skills and ability to work independently as well as part of a team.
• Strong communication skills, both written and verbal, with the ability to communicate complex technical concepts to non-technical stakeholders.

Desired Skills

• Exposure to machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Leverage Azure Machine Learning to manage data pipelines, experiments, and deployments.
• Exposure to implementing end-to-end AI solutions using Azure AI services and Azure Cognitive Services.
• Certification in Microsoft Azure AI relative to Azure Machine Learning
• Expert database knowledge in SQL
• Proficiency in Azure Data Services (Data Factory, Synapse Analytics).