Data Scientist

Overview:

As a Data Scientist with 3-4 years of professional experience, you will work on data-driven projects that impact key business decisions. You will collaborate with cross-functional teams to analyze large datasets, build predictive models, and deliver insights that drive business outcomes. Your experience with Qlik AutoML will be essential in automating machine learning workflows and delivering value to our stakeholders.

Key Responsibilities:

• Data Analysis & Preparation: Collect, clean, and prepare large datasets from multiple sources for analysis. Apply statistical techniques to analyze trends, patterns, and anomalies.

• Machine Learning & Model Development: Design, build, and evaluate predictive models using machine learning algorithms (e.g., regression, classification, clustering). Implement automation strategies using Qlik AutoML to optimize model building processes.

• Qlik AutoML Expertise: Leverage Qlik AutoML to automate machine learning tasks such as feature selection, model training, and hyperparameter tuning. Provide recommendations on best practices and integration for scalable ML deployment.

• Data Visualization & Reporting: Create interactive dashboards and reports using tools such as Qlik, Tableau, or Power BI. Present actionable insights to stakeholders in a clear, concise manner.

• Collaboration & Communication: Work closely with business leaders, analysts, and engineers to understand business requirements and translate them into data science solutions. Communicate complex results and strategies to non-technical stakeholders.

• Continuous Learning & Improvement: Stay updated with the latest advancements in machine learning and AI. Contribute to improving the internal data science processes, techniques, and methodologies.

Skill & Qualification:

• Education: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Experience: 3-4 years of hands-on experience in Data Science, with a proven track record of building and deploying machine learning models.
• Technical Skills:
  • Strong knowledge of machine learning algorithms and statistical methods (e.g., regression, decision trees, clustering, etc.).
  • Proficiency in Python, R, or similar programming languages.
  • Experience with Qlik AutoML, including model development, automation, and deployment.
  • Familiarity with data visualization tools (e.g., Qlik Sense, Tableau, Power BI).
  • Solid experience with data manipulation and analysis using libraries such as pandas, NumPy, scikit-learn, etc.
• Problem-solving & Analytical Skills: Ability to tackle complex business problems and deliver actionable insights.
• Communication Skills: Strong verbal and written communication skills with the ability to explain technical concepts to non-technical stakeholders.
• Collaboration: Proven ability to work effectively in cross-functional teams and manage multiple priorities in a fast-paced environment.