Cognizant is hiring for a fresher entry level Data Scientist role in India

Position:

• AIML Data Scientist

Company:

• Cognizant

Location:

• Indore

Job type:

• Full-time

Job mode:

• Hybrid

Job requisition id:

• 00062679901

Years of experience:

• Not explicitly mentioned; looks like a fresher entry level job as per the JD

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Company Description

• Cognizant is a prominent global leader in IT services and consulting, known for empowering enterprises with digital capabilities to boost their competitiveness.

• With over 300,000 employees globally, the company fosters a vibrant, inclusive, and collaborative work culture that emphasizes innovation and excellence.

• Its core philosophy revolves around a people-centric approach, where both employees and clients are supported and encouraged to grow and succeed.

• Cognizant stands as a digital transformation expert, seamlessly integrating technology, operations, and strategic solutions to cater to business challenges in a wide array of industries.

• Headquartered in the United States, the company’s global reach and technical expertise help clients reimagine and build future-ready enterprises.

• It has been recognized on numerous global platforms, including Forbes World’s Best Employers list for 2024.

• Cognizant not only promotes business agility but also invests in corporate social responsibility initiatives, aiming to positively impact communities, climate, and corporate governance.

• Diversity, equity, and inclusion are pillars of its work environment, encouraging everyone to thrive, regardless of background.

• By continuously exploring advancements in AI, ML, and digital strategy, Cognizant positions itself as a reliable partner in the journey of digital evolution.

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Profile Overview

• This position calls for a data scientist proficient in Artificial Intelligence and Machine Learning (AI/ML), tasked with designing, developing, and deploying deep learning solutions to solve business challenges.

• The ideal candidate will have a hands-on approach to problem-solving and exhibit a consultative mindset to apply advanced AI techniques efficiently.

• The role requires blending technical modeling with practical business insight to estimate and deliver measurable business value through model deployment.

• Candidates should be able to apply a variety of machine learning and deep learning algorithms, optimizing them for maximum performance and accuracy.

• The professional must collaborate closely with domain and customer-facing teams to understand business needs, interpret data dictionaries, and recommend tailored AI-driven solutions.

• Familiarity with modern data engineering and data preprocessing practices is essential for building robust models.

• The role involves actively engaging in feature engineering, model training, and evaluation, particularly using Python, R, SQL, and cloud-based data pipelines.

• Emphasis will be placed on model interpretability, visualization, and validation using business intelligence tools.

• Experience in deploying scalable AI models using cloud or hybrid infrastructures and integrating them with business applications will be a core part of the responsibilities.

• The position also demands proactive learning and contribution to internal knowledge-sharing, such as whitepapers, demos, and model showcases.

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Qualifications

• Must possess hands-on expertise in AI/ML with the capability to design and refine algorithms tailored for specific business problems.

• Should be adept in model development, especially involving deep learning frameworks like TensorFlow and PyTorch.

• Strong programming knowledge in Python, R, and SQL is essential, along with proficiency in handling data pipelines and pre-processing techniques.

• Proven experience with NLP applications such as text classification, named entity recognition, relationship extraction, summarization, semantic search, and reasoning using tools like Spacy and other open-source libraries.

• Must understand computer vision applications and be capable of developing models for image and video data using OpenCV and similar tools.

• Should be comfortable working with unstructured data formats such as speech, image, text, and video.

• Deep knowledge of advanced AI/ML algorithms and the ability to choose the best-suited methods for each unique use case is crucial.

• Familiarity with visualization tools like Power BI and Tableau to evaluate, validate, and communicate results is necessary.

• Cloud deployment expertise is important, with hands-on knowledge of building CI/CD pipelines and deploying models in test/control frameworks.

• Should have experience integrating models into real-world applications through REST APIs and similar interfaces.

• Experience with platforms like Azure ML, IBM Watson, AWS Sagemaker, and Google Cloud is advantageous.

• Additional skills in Pyspark, Hadoop, reinforcement learning, and optimization algorithms will be valuable.

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Additional Info

• Candidates should have a deep understanding of machine learning theory, statistical analysis, and mathematical foundations relevant to AI modeling.

• Expected to continuously update skills and stay abreast with advancements in the AI/ML domain through self-learning, community participation, and active experimentation.

• Prior contributions to open-source projects or participation in competitive platforms like Kaggle will be considered a strong asset.

• Working knowledge of GPU-based computing, microservices architecture, and modern data processing tools is highly desirable.

• Appreciation for data security, digital ethics, privacy regulations, and responsible AI practices is a must-have in today’s AI landscape.

• Experience in building scalable and production-ready AI solutions is preferred, especially for enterprise-level implementation.

• Understanding of modern computing paradigms such as edge computing, stream data processing, RPA (Robotic Process Automation), and AR/VR will add further value.

• Familiarity with version control systems and collaborative development platforms like Git and GitHub is important for teamwork and reproducibility.

• Demonstrated ability to articulate ideas and model outcomes clearly to stakeholders across technical and non-technical teams.

• Ability to estimate the tangible business impact of deployed AI solutions and track performance using appropriate frameworks.

• Cognizant encourages a growth-oriented mindset and values those who contribute to knowledge repositories, whitepapers, and innovative solution assets.

• The role may occasionally involve presenting your work or outcomes in large forums, requiring excellent communication and presentation skills.

• Candidates should exhibit curiosity, a forward-thinking attitude, and a readiness to collaborate beyond their core technical responsibilities.

Please click here to apply.

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