Senior / Lead Data Scientist

We are looking for an experienced Data Scientist with 4-8 years of expertise across diverse industries suchas telecommunications, finance, and retail. This role involves leveraging machine learning (ML), deeplearning (DL), and natural language processing (NLP) to drive impactful business solutions. A strong
background in data science, combined with hands-on experience in both technical implementationandbusiness impact projects, is essential. Candidates with telecommunications experience will be preferred

Key Responsibilities:

1. Data Science and Machine Learning:

Develop and deploy ML/DL models to address complex business challenges such as
predictive analytics, customer segmentation, and personalization. o Implement algorithms using frameworks such as TensorFlow, PyTorch, Scikit-learn, andXGBoost for classification, regression, and forecasting tasks.

2. Natural Language Processing (NLP) and Generative AI:

Design and deploy advanced NLP solutions, including document QA systems andAI- driven chatbots. o Leverage state-of-the-art frameworks like LangChain, Hugging Face, and LlamaIndex tofine-tune transformer-based LLMs for text generation, summarization, and informationretrieval.

3. Data Engineering and Visualization:

Build robust pipelines using Python and PySpark to preprocess and analyze large datasetsefficiently.
Create visually compelling dashboards and tools using Power BI and Streamlit to communicate insights effectively to stakeholders.

4. Cloud Platforms and Deployment:

Utilize cloud services such as AWS (SageMaker, Kinesis), Azure, or GCP to build scalableand secure data pipelines and deploy ML models. o Work with containerization and orchestration tools like Docker and Kubernetes for scalable deployments.

5. Collaboration and Impact:

Collaborate with cross-functional teams to understand business needs and translatetheminto data-driven solutions. o Present findings and recommendations to both technical and non-technical audiences toinfluence decision-making.

Required Qualifications:

Experience:
4-8 years of experience in data science roles with exposure to diverse industries such as telecommunications, finance, or retail. Telecommunications experience is a strong plus. o Demonstrated success in both technical implementation (building models, pipelines) andachieving measurable business impact (increased revenue, improved efficiency).

Technical Skills:
Programming: Advanced proficiency in Python, SQL, and PySpark for data manipulationand model development. o Machine Learning: Expertise in ML/DL frameworks, including TensorFlow, PyTorch, XGBoost, and Scikit-learn. o NLP and GenAI: Experience with LangChain, Hugging Face, LlamaIndex, and transformer- based LLMs for NLP applications. Visualization and

Tools:
Proficiency in creating dynamic visualizations using Power BI and Streamlit. o Experience with version control systems (Git) and ML lifecycle tools (MLflow).

Cloud Platforms:
Strong familiarity with AWS (SageMaker, Kinesis), Azure, or Google Cloud for end-to-endmachine learning workflows.

Specialized Skills:
Advanced NLP capabilities, particularly in building document QA systems and conversational AI solutions. Preferred Attributes: Problem-solving mindset with a focus on delivering measurable business value.

Strong communication and collaboration skills to work effectively with stakeholders and cross functional teams.

A proactive attitude towards learning and applying emerging technologies in AI and machine learning. Scope of Growth with 6d:
This role is growth oriented. Once initial flair is demonstrated as successful project(s), you will leada team and will be responsible for cutting edge work on creating new modelsto solve problems. You will also need to coach and guide a team on machine learning technologies, frameworks and languages.