Top Data Science Jobs in Hyderabad

Builds corporate hiring partnerships with technology companies, pitches talent acquisition proposals, and organizes recruitment drives. Manages end-to-end student placement processes, tracks placement KPIs, and collaborates with academic and operations teams to improve interview readiness. Provides guidance on resumes, LinkedIn profiles, mock interviews, and placement etiquette while monitoring technology-sector hiring trends and in-demand skills.

Drive inbound and outbound sales for technology training and certification programs. Counsel prospective learners, understand career goals, recommend suitable courses, manage lead qualification through closing, conduct follow-ups across calls, WhatsApp, and email, maintain CRM records, build learner relationships, and achieve monthly enrollment and revenue targets. The role requires EdTech and IT course-selling experience, strong communication and negotiation skills, and availability for a US shift.

Drive inbound and outbound sales for technology training programs, counsel prospective learners, recommend courses based on career goals, manage lead qualification through enrollment, conduct follow-ups across phone, WhatsApp, and email, maintain CRM records, build prospect relationships, and achieve monthly sales and revenue targets.

Develops full-stack AI and machine learning applications using web technologies, statistical modeling, deep learning, databases, cloud platforms, and APIs. Designs algorithms, translates technical specifications into code, performs testing and debugging, documents solutions, and improves product and system performance. Works independently on complex initiatives, collaborates with stakeholders, mentors colleagues, and may manage projects or review others’ work.

Develop end-to-end data science and AI/ML solutions involving statistical modeling, machine learning, generative AI, LLMs, NLP, and unstructured data analytics. Build data models and algorithms, solve ambiguous business problems, collaborate with project managers and multiple teams, and deliver actionable insights using cloud platforms such as AWS, Azure, or GCP. Present findings and communicate effectively with technical and business stakeholders.

Lead design and delivery of NLP and Generative AI solutions, from problem definition through deployment. Build and fine-tune transformers and LLMs for summarization, QA, classification and chatbots, apply classical and deep learning methods, ensure scalable reproducible ML workflows in cloud environments, mentor junior data scientists, and collaborate with product and engineering to translate business problems into AI solutions.

Apply statistical and machine learning methods to marketing datasets to build segmentation, propensity, attribution, LTV, and personalization models. Clean and structure client data, translate business questions into analytical approaches, present findings to stakeholders, and collaborate to operationalize models into marketing platforms and production workflows.

Lead AI and data innovation by developing ML models, optimizing data systems, and mentoring junior team members in a collaborative team environment.