الوصف الوظيفي
Project Role : Data Science Practitioner
Project Role Description : Formulating, design and deliver AI/ML-based decision-making frameworks and models for business outcomes. Measure and justify AI/ML based solution values.
Must have skills : Data Science
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As a Data Science Practitioner, you will be engaged in formulating, designing, and delivering AI and machine learning-based decision-making frameworks and models that drive business outcomes. Your typical day will involve collaborating with cross-functional teams to understand business needs, analyzing data to derive insights, and presenting your findings to stakeholders to support strategic decisions. You will also measure and justify the value of AI and machine learning solutions, ensuring they align with organizational goals and deliver tangible results.
Roles & Responsibilities:
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work related problems.
- Analyze complex datasets to extract actionable insights that inform business strategies.
- Collaborate with stakeholders to define project requirements and deliverables.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Data Science.
- Strong understanding of machine learning algorithms and their applications.
- Experience with data manipulation and analysis using programming languages such as Python or R.
- Familiarity with data visualization tools to effectively communicate findings.
- Ability to work with large datasets and perform statistical analysis.
Additional Information:
- The candidate should have minimum 3 years of experience in Data Science.
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
لقد تمت ترجمة هذا الإعلان الوظيفي بواسطة الذكاء الاصطناعي وقد يحتوي على بعض الاختلافات أو الأخطاء البسيطة.
