Data Scientist

Job Description:

We are seeking a dynamic Data Scientist / Machine Learning Engineer with 26 years of experience from a premier institute to join our team. In this role, you will design, develop, and implement advanced data models and algorithms, transforming raw data into actionable insights and scalable AI solutions.

The ideal candidate will apply their expertise in statistical analysis to derive meaningful insights from complex datasets, contributing to informed decision-making processes. The role involves employing advanced techniques to assess and enhance the performance of machine learning models, ensuring accuracy and reliability.

Responsibilities:

Data Analysis and Modeling

• Analyze structured and unstructured data to derive insights and identify patterns.
• Apply statistical analysis expertise to extract meaningful insights from complex datasets.
• Design and implement machine learning models for predictive analytics, classification, regression, and clustering tasks.
• Contribute to informed decision-making processes by providing actionable insights.
• Design, implement, and deploy data science solutions with a focus on efficiency and scalability.

Machine Learning Engineering

• Develop, train, and optimize ML models and deploy them to production environments.
• Assess and enhance the performance of machine learning models using advanced techniques.
• Build scalable and efficient pipelines for data preprocessing and model deployment.
• Utilize strong proficiency in Python to develop robust and scalable machine learning models.
• Leverage Jupyter notebooks and AWS SageMaker for collaborative and cloud-based development.

Collaboration

• Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define project goals and deliver solutions.
• Translate complex technical findings into actionable insights for non-technical stakeholders.

Innovation and Experimentation

• Stay updated with the latest trends in AI/ML, propose innovative solutions, and lead proof-of-concept initiatives.
• Continuously improve model performance by experimenting with new techniques and tools.

Operational Excellence

• Monitor and maintain deployed models, ensuring reliability, scalability, and performance.
• Conduct thorough documentation of workflows, models, and methodologies.

Qualifications:

Educational Background

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field from a premium institute (e.g., IITs, NITs, IIITs, or global equivalents).

Experience

• 2–6 years of professional experience in data science, machine learning, or a related field.

Technical Skills

• Proficiency in Python or R, with strong expertise in libraries such as NumPy, Pandas, TensorFlow, PyTorch, or Scikit-learn.
• Experience with SQL and data querying.
• Hands-on experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and MLOps tools (e.g., Docker, Kubernetes, MLflow).
• Familiarity with big data technologies like Spark, Hadoop, or similar.
• Strong understanding of algorithms, statistics, and data visualization tools (e.g., Tableau, Power BI).

Soft Skills

• Strong problem-solving skills and analytical thinking.
• Excellent verbal and written communication skills.
• Ability to work both independently and collaboratively in a fast-paced environment.

If you are a skilled ML Engineer with a passion for applying statistical analysis to create impactful machine learning solutions, and you possess the required skills and experience, we invite you to apply for this exciting opportunity.