Job Description

Note: Make sure all your previous candidates are completing the Assignment.

Note: Required only Local candidates [Look from anywhere from Karnataka]

Position: Data Scientist

Exp: 5-8 Years

Location: Bangalore ( Only Bangalore Candidates )

NP: Only Immediate/10Days

Basic Qualifications:

• Proficiency in programming languages such as Python, SQL, R etc .
• Bachelor or Master's degree in highly quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
• 4-6 years of academic and relevant industry experience.
• Proven experience as a Data Scientist with a strong portfolio of data science projects.
• Experience in a specific industry (e.g., Edtech, finance,retail) is advantageous.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
• Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, D3.js).
• Hands-on experience with Databricks for big data processing and analytics.
• Proficiency with the Elastic Stack (Elasticsearch & Kibana) for search and data analysis is a plus.
• Analytical Skills: Strong ability to analyze complex data sets, identify trends, and draw actionable conclusions.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical information to non-technical stakeholders.
• Problem-Solving: Demonstrated ability to tackle complex problems and develop innovative solutions.

Preferred Qualifications:

• Bachelor's, Master's or PhD degree in CS, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least 3 years of working experience as a Data Scientist.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of advanced machine learning techniques (e.g., deep learning, natural language processing).
• Familiarity with business intelligence tools and methodologies.

Position Overview:

We are seeking a highly skilled Data Scientist to join our team. The ideal candidate will have a strong background in data analysis, statistical modeling, and machine learning, coupled with excellent problem-solving abilities and a keen business sense. You will work closely with cross-functional teams to extract insights from complex datasets and drive data-driven decision-making.

Key Responsibilities:

• Data Analysis: Collect, clean, and preprocess large datasets from various sources. Perform exploratory data analysis to uncover patterns and insights.
• Statistical Modeling: Develop and implement statistical models and algorithms to address business problems. Validate models and perform performance evaluations.
• Machine Learning: Design, train, and deploy machine learning models to predict outcomes and automate processes. Continuously improve model accuracy and efficiency.
• Collaboration: Work with data engineers, analysts, and other team members to understand business requirements and provide data-driven solutions.
• Continuous Learning: Stay updated with the latest industry trends, technologies, and best practices in data science and machine learning.

If interested please share your resume with Khushi@hr-hyre.com OR contact us @99029 68612.

Job Types: Full-time, Permanent

Pay: ?1,500,000.00 - ?3,000,000.00 per year

Benefits:

• Health insurance
• Provident Fund

Schedule:

• Day shift

Supplemental Pay:

• Performance bonus
• Yearly bonus

Application Question(s):

• Must-Have:
• Proficiency in programming languages such as Python, SQL, R etc.
• Must-Have:
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn).
• Must-Have:
• Hands-on experience with Databricks for big data processing and analytics.
• Must-Have:
• Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
• Must-Have:
• Knowledge of data visualization tools (e.g., Matplotlib, Seaborn, D3.js).

Experience:

• Data Scientist: 7 years (Preferred)

Location:

• Bengaluru, Karnataka (Preferred)

Work Location: In person