Data Analyst + Machine Learning

We are seeking a highly analytical and technically skilled Data Analyst with hands-on experience in Machine Learning to join our team. The ideal candidate will be responsible for analyzing large datasets, generating actionable insights, and building ML models to drive business solutions and innovation.

Key Responsibilities:

• Collect, clean, and analyze structured and unstructured data from multiple sources.
• Develop dashboards, visualizations, and reports to communicate trends and insights to stakeholders.
• Identify business challenges and apply machine learning algorithms to solve them.
• Build, evaluate, and deploy predictive and classification models using tools like Python, R, Scikit-learn, TensorFlow, etc.
• Collaborate with cross-functional teams including product, marketing, and engineering to implement data-driven strategies.
• Optimize models for performance, accuracy, and scalability.
• Automate data processing and reporting workflows using scripting and cloud-based tools.
• Stay updated with the latest industry trends in data analytics and machine learning.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
• 2+ years of experience in data analytics and machine learning.
• Strong proficiency in SQL, Python (Pandas, NumPy, Scikit-learn), and data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn.
• Experience with machine learning techniques such as regression, classification, clustering, NLP, and recommendation systems.
• Solid understanding of statistics, probability, and data mining concepts.
• Familiarity with cloud platforms like AWS, GCP, or Azure is a plus.
• Excellent problem-solving and communication skills.

Job Types: Full-time, Permanent

Pay: ₹10,000.00 - ₹15,000.00 per month

Ability to commute/relocate:

• Kalighat, Kolkata, West Bengal: Reliably commute or planning to relocate before starting work (Preferred)

Language:

• English (Preferred)

Work Location: In person