Lead Data Scientist
3 weeks ago
Job Title : Lead Data Scientist
Experience Level : 5-7 years as Data Scientist
Location : Bengaluru / Chennai
Job Summary :
Lead Data Scientist is a highly skilled Data Scientist that possess 10 - 15 years of overall experience working across Financial Services, Healthcare, Insurance, and Manufacturing Domain in firms specializing in Data and analytics and at least 5 -7 years of experience as Data Scientist.
They will have a Bachelor 's or Master 's degree in Computer Science, Data Science, Statistics, or a related field and proven experience as a Data Science Developer, Data Scientist, or similar role. They will play a key role in evaluating options, building & helping the team build the model right way.
Responsibilities :
- Use statistical and machine learning techniques to develop GenAI (LLM, Agents, RAG), Predictive models, algorithms, and data products.
- Work with complex data sets to extract insights and develop actionable recommendations for business stakeholders.
- Design, develop and implement machine learning pipelines and production-ready systems that manage high traffic and real-time data.
- Design and implement predictive models to support business decisions and enhance operational efficiencies.
- Collaborate with cross-functional teams to integrate data science models into business systems and applications.
- Define and execute data strategies that align with business objectives and ensure data integrity, quality, and governance.
- Collaborate multiple teams to design robust data pipelines, ensuring seamless integration and transformation of data from various sources.
- Lead team of data scientists and coordinate with business stakeholders with ownership on committed deliverables.
- Create and maintain documentation on data science models, algorithms, and pipelines.
- Keep up to date with the latest developments in machine learning, data science, and related fields and apply them to business problems as needed.
- Utilize deep domain knowledge to understand business needs and translate them into data-driven solutions.
- Sharing of knowledge and best practices among team members.
- Develop natural language processing, text understanding, classification, pattern recognition, recommendation, targeting, ranking, or similar systems.
- Troubleshoot and solve issues with data pipelines, machine learning models, and data systems.
- Confidential & Proprietary to ConceptVines
- Develop and maintain APIs for model deployment.
- Foster a culture of continuous learning and improvement, staying abreast of advancements in data science methodologies and tools.
- Evaluate and implement modern technologies and techniques to enhance the efficiency and effectiveness of data analysis processes.
Requirements :
- Bachelor 's or Master 's in Computer Science, Data Science, Statistics, or a related field:
- Fundamental for understanding the theoretical aspects of the role.
- Exceptional understanding of machine learning algorithms, Model Design processes, tools, and platforms.
- Deep Understanding in Hyperparameter Tuning, Model Optimization / Debugging techniques, Explainability, Drift Management, Bias Detection
- Proven experience as a Data Science Developer, Data Scientist, or similar role.
- Strong knowledge of Python programming and building APIs.
- Proficient in SQL and experience with big data platforms like Hadoop, Spark, or similar technologies.
- Strong mathematical skills (e.g., statistics, algebra): Fundamental for data modeling and analysis.
- Expertise in LLMs - OpenAI, Gemini, CoPilot etc.
- Good Knowledge of RAG Pipeline Architectures
- Fine/Prompt/Instruction Tuning of LLMs
- Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
- Experience with cloud services (GCP, Azure, AWS).
- Strong experience in data wrangling, data cleaning, data preprocessing, and data visualization using tools such as Pandas, NumPy, Matplotlib.
- Experience with distributed data/computing tools.
- Knowledge of database systems such as MySQL, MongoDB, and PostgreSQL and familiarity with SQL and NoSQL databases.
- Experience with natural language processing (NLP) techniques such as sentiment analysis, text classification, and topic modeling, and proficiency in using NLP libraries such as NLTK, spaCy, and Gensim.
- They will be proficient in statistical analysis, hypothesis testing, and data modeling to derive actionable insights from complex data sets.
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