Data Science- Consultant

Job Summary The Data Scientist will be responsible for turning complex datasets into actionable insights that drive strategic business decisions. This role involves applying statistical analysis, machine learning techniques, and data modeling to solve business problems, optimize processes, and support product and strategy teams with data driven recommendations.

Key Responsibilities

• Collect, clean, and preprocess structured and unstructured data.
• Build, test, and deploy machine learning models (supervised, unsupervised, NLP, time series, etc.).
• Develop predictive and prescriptive analytics solutions.
• Work closely with cross functional teams (Product, Engineering, Marketing, Finance, Operations) to identify analytical opportunities and Translate business problems into analytical frameworks and data solutions.
• Present insights, dashboards, and recommendations to technical and non technical stakeholders.
• Collaborate with data engineering teams to build and optimize data pipelines.
• Ensure data quality, reliability, and scalability across systems and platforms and Automate data workflows where needed.
• Develop visualizations using tools like Power BI, Tableau, or custom dashboards and Communicate insights effectively using storytelling techniques.
• Deploy ML models into production environments, monitor model performance and retrain/improve models as required.
• Maintain documentation of methodologies, experiments, and results.

Required Qualifications

• Bachelor’s or master’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, or related fields.
• 6 -8 years of experience in data science, analytics, or machine learning roles.
• Strong programming skills in Python.
• Experience with ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost.
• Strong SQL skills and understanding of relational databases.
• Hands-on experience with cloud platforms (Azure, AWS, GCP).
• Proficiency in data visualization tools (Power BI, Tableau, matplotlib, seaborn, etc.).