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Lead Data Scientist

2 months ago

Bangalore, Karnataka, India Selsoft Full time

Responsibilities :

- 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.

- 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 dat 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.

(ref:hirist.tech)