Grazitti Interactive - Data Scientist

Job Description :

We are seeking a seasoned and highly analytical Data Scientist with 5-7 years of professional experience to join our dynamic data science team.

The ideal candidate will be a technical expert and a strategic thinker, capable of turning complex datasets into actionable insights and robust predictive models.

You will play a key role in the entire data science lifecycle, from problem definition and data exploration to model development, validation, and deployment.

Expertise in both traditional statistical modeling and modern deep learning techniques, including Generative AI, is highly valued.

Key Responsibilities Solving & Strategy :

• Collaborate with stakeholders across business units (e.g., Product, Marketing, Operations) to identify key business questions and formulate data-driven solutions.
• Translate business needs into a clear, structured data science problem and define the project scope, objectives, and success metrics.
• Drive strategic initiatives by providing data-backed recommendations to senior Analysis & Modeling :
• Perform exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for modeling.
• Develop, implement, and validate machine learning models (e.g., classification, regression, clustering, time series analysis) to solve complex business problems.
• Design and conduct experiments (A / B testing) to measure the impact of new features or AI & Advanced Techniques :
• Research, evaluate, and apply advanced deep learning techniques, including Generative AI models (e.g., Large Language Models, Diffusion Models), to create innovative solutions.
• Develop and implement strategies for prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning models to enhance performance and contextual relevance.
• Stay current with the latest research and trends in AI and machine learning, and assess their applicability to our business & Collaboration :
• Clearly communicate findings, methodologies, and the impact of models to both technical and non-technical audiences through reports, dashboards, and presentations.
• Partner with Data Engineers to build scalable data pipelines and with MLOps Engineers to deploy models into production.
• Mentor junior data scientists and contribute to a culture of continuous learning and data literacy within the & Tooling :
• Write production-quality code in Python for data analysis, modeling, and automation.
• Utilize version control systems (e.g., Git) and collaborate effectively on shared codebases.
• Proficiency with relevant data science tools and platforms (e.g., SQL, cloud platforms like AWS, Azure, Qualifications : : Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or a related : 5-7 years of hands-on experience as a Data Scientist or in a similar role, with a strong portfolio of projects that have been successfully deployed and delivered measurable business Skills : Expert proficiency in Python and its data science ecosystem (Pandas, NumPy, SciPy, Learning : Deep understanding of a wide range of ML algorithms and statistical modeling Learning : Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and an understanding of neural network AI : Practical experience with Large Language Models (LLMs), prompt engineering, and fine-tuning. Familiarity with other generative models is a Querying : Strong SQL skills are a : Proven ability to define and solve complex, ambiguous problems with an analytical and methodical : Excellent written and verbal communication skills, with the ability to present complex technical concepts clearly and concisely to diverse Qualifications (Bonus Points) :
• Experience with MLOps principles and tools (e.g., MLflow, Kubeflow).
• Proficiency with cloud-based data warehouses and services (e.g., Snowflake, BigQuery, Redshift, S3).
• Experience with distributed computing frameworks (e.g., Spark, Dask).
• Experience in [specific industry, e.g., FinTech, Healthcare, E-commerce, SaaS].
• Publications in peer-reviewed journals or major conferences.

(ref : hirist.tech)