Tredence
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Pune · On-site · 7-10 Yrs · Aug 21
Business consulting · 1001 to 5000 Employees · San Jose, US
As with every marathon, the last mile is the toughest. It is here that enterprises lose the strength and resolve to take analytics beyond insight generation and use them to generate value. That’s where we saw a gap waiting to be filled - in activating data and operationalizing insights for real, tangible business impact. We’re focused on bridging the gap between insights delivery and value realization, partnering with our clients to help them cross the last-mile gap in analytics. This DNA pushes our ecosystem to go beyond possible, helping our clients re-think their limitations and overcome their norms of ‘possible’.
Hiring: Engineering
What employees say
+ Enthusiastic and ambitious work culture. Tredence enables everyone with the tools, means and the backing one needs to succeed and grow.
− As a fast growing organization, baseline expectations would be to learn and adapt fast, be on the toes and fail fast. Not a con but the rapid pace in work is not for all.
More reviews on the company profile.
Interview experience · Data Engineer
It was very easy with basic dsa in your preferred language and basic sql concepts like joins. Prepare basic dsa and sql it will help to get on interview process
Very_easy difficulty · Chennai · 440 reports
More interview insightsJob description
Overview
Data Science Manager - Generative AI
Responsibilities
- Lead, mentor, and grow a team of data scientists working on GenAI and advanced ML initiatives
- Define GenAI roadmap aligned with business and product strategy
- Translate ambiguous business problems into actionable AI solutions
- Drive best practices for model development, evaluation, and deployment
- Design and oversee solutions using LLMs, embeddings, RAG pipelines, fine-tuning, and prompt engineering
- Evaluate and select foundation models (OpenAI, Anthropic, open-source models, etc.)
- Guide experimentation with multimodal AI (text, image, audio, video)
- Ensure model quality, robustness, fairness, and explainability
- Partner with engineering to deploy GenAI systems at scale
- Establish MLOps standards: versioning, monitoring, retraining, and cost optimization
- Ensure performance, latency, security, and reliability of GenAI systems
- Work closely with Product Managers to define AI-driven features and success metrics
- Communicate complex AI concepts to non-technical stakeholders and executives
- Support go-to-market and customer-facing GenAI capabilities
- Implement responsible AI practices, including privacy, compliance, and risk mitigation
- Ensure ethical use of GenAI models and adherence to regulatory standards
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field
- 7+ years of experience in data science, machine learning, or AI roles
- 2+ years of people management or technical leadership experience
- Strong hands-on experience with Generative AI and LLMs
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)
- Solid understanding of statistics, experimentation, and model evaluation
- Familiarity with vector databases (FAISS, Pinecone, Weaviate, Milvus)
- Background in NLP, conversational AI, or search/recommendation systems
- Python, Machine Learning, GenAI, LLM, RAG, Agentic AI
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