Level - Specialist / Senior Specialits 

Experience – 6+Years

Location- Bangalore, Chennai, Hyderabad, Noida

Job Title - AI Data scientist

Role - Artificial intelligence (AI)

Primary Skil l- Programming Language Python

 

About us: 

Qualitest, The World’s Leading AI-Powered Quality Engineering Company

Qualitest is the world’s leading managed services provider of AI-led quality engineering solutions. It helps brands transition through the digital assurance journey and make the move from conventional functional testing to adopt innovations such as automation, AI, blockchain, and XR.

Qualitest’s core mission is to mitigate business risks associated with digital adoption. It fulfills this through customized quality engineering solutions that leverage Qualitest’s deep, industry-specific knowledge for various sectors, including technology, telecommunications, finance, healthcare, media, utilities, retail, manufacturing, and defense. These scalable solutions protect brands through end-to-end value demonstration with a focus on customer experience and release velocity.

A pioneer and innovator in its industry, Qualitest has been recognized in the highest Leader position in Everest Group's Quality Engineering Services for Mid-market Enterprises PEAK Matrix® Assessment 2024 report and has also been recognized as a Leader in The Forrester Wave™️: Continuous Automation and Testing Services Q2 2024 report.

Qualitest has offices in the United States, United Kingdom, Israel, Romania, India, Mexico, Portugal, Switzerland, and Argentina

 

Role & Responsibility

We are seeking a Data Scientist to provide our clients with valuable insights derived from data analysis. The ideal candidate will have expertise in working with large datasets to identify opportunities for process optimization, as well as experience using models to test the effectiveness of various actions. The role involves developing new AI/ML use cases based on client data. The successful candidate will be highly skilled in data mining and analysis techniques, the use of diverse data tools, building and implementing models, creating algorithms, and running simulations. They must have a proven track record of using data-driven insights to drive business results. Comfort working with various stakeholders and cross-functional teams is essential. A passion for discovering hidden solutions in data and improving business outcomes is key.

Responsibilities for Data Scientist:

Collaborate with stakeholders across the organization to identify opportunities for leveraging company data to drive business solutions.

Analyze data from client databases to optimize use case development, marketing strategies, and overall business performance.

Evaluate the effectiveness and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms tailored to specific datasets.

Apply predictive modeling to enhance QA and other business outcomes.

Build and implement an A/B testing framework, ensuring high-quality model testing.

Work with cross-functional teams to implement models and track results.

Develop processes and tools to monitor, assess, and improve model performance and data accuracy.

Must-Have Qualifications:

Over 8 years of experience in Data Science and AI/ML, with a total IT experience of 12+ years.

Proficiency in R language is required.

Ability to quickly learn and effectively use new AI/ML tools.

Solid experience with advanced machine learning algorithms and statistical techniques, including regression, simulation, scenario analysis, modeling, clustering, decision trees, and neural networks.

Demonstrated experience in data retrieval from SDLC systems and analytic reporting databases.

Familiarity with databases and database query languages like MySQL, Access, and SQL; experience with Python and other programming languages.

Strong interpersonal skills with the ability to interface effectively with clients and collaborate constructively with teams.

Excellent verbal and written communication skills.

Experience with cloud computing environments and data science tools such as AWS, SageMaker, GCP, and Databricks.

Familiarity with NLP algorithms like LSA, LDA, and QNLI, and tools like JIRA, Confluence, and GitHub. Knowledge of software engineering and structured software development practices.

Proven ability to perform statistical data analysis.

Key Skills:

Data Science: 4/5

AI/ML: 4/5

R Language: 3/5