Data Scientist - Python / SQL

Description : About the Role :

We are seeking a highly skilled and motivated Data Scientist to join our growing data consulting team.

In this role, you will work closely with clients' senior stakeholders and cross-functional teams to uncover actionable insights, build predictive models, and deliver data-driven solutions that drive business value.

The ideal candidate is an analytical thinker, strong communicator, and has hands-on experience with large datasets, machine learning algorithms, and advanced statistical techniques.

Youll work across diverse projects in industries such as finance, healthcare, retail, and more helping organizations turn their data into strategic assets.

Your Team :

As a key member of the Data Consulting Team, you will collaborate with a dynamic group of data scientists, engineers, analysts, and consultants.

Youll work alongside partners, project managers, and technology leads to solve high-impact problems using modern data science techniques.

Key Responsibilities :

• Design, develop, and implement end-to-end data science solutions tailored to business problems.
• Analyze complex datasets using Python, R, SQL, and other relevant tools to extract insights and build predictive models.
• Develop and evaluate machine learning models for classification, regression, segmentation, recommendation systems, and NLP use cases.
• Work with large-scale distributed data systems such as Hadoop, Spark, and cloud platforms (AWS, Azure, GCP).
• Apply advanced statistical analysis and mathematical modeling techniques to interpret data trends and patterns.
• Collaborate with data engineers to ensure seamless data pipeline integration and model deployment.
• Translate complex data science concepts into clear business insights for non-technical stakeholders.
• Create compelling data visualizations and present insights using tools like Tableau, Power BI, or matplotlib / seaborn.
• Author and review analytical solution proposals and technical documentation for internal and client use.
• Engage in code reviews, knowledge sharing, and mentoring junior data scientists.
• Continuously research and prototype new algorithms, tools, and frameworks to improve analytical capabilities.

Required Skills & Experience :

1. Regression, Classification, Clustering, Time Series

2. Random Forest, Gradient Boosting, SVM, KNN

3. Deep Learning : CNN, RNN, LSTM, Transfer Learning

4. NLP : Named Entity Recognition, LSA, Tokenization, Lemmatization, etc.

(ref : hirist.tech)