Data Scientist

Job summary

Collect, clean, process, and analyze datasets; develop, evaluate, deploy, and monitor machine learning and statistical models to address business problems. Communicate findings through dashboards, reports, and documentation, and collaborate with analysts, engineers, and stakeholders.

Job details

Key Responsibilities Collect, clean, process, and analyze large datasets. Develop and implement Machine Learning models. Perform exploratory data analysis (EDA) to identify trends and patterns. Build predictive and statistical models to solve business problems. Apply supervised and unsupervised learning techniques. Develop data-driven solutions using Python and SQL. Perform feature engineering and model optimization. Evaluate model performance using appropriate metrics. Create dashboards and reports to communicate insights. Collaborate with business analysts, engineers, and stakeholders. Deploy and monitor Machine Learning models. Document methodologies, findings, and project outcomes. Preferred Skills Strong programming knowledge in Python or R. Hands-on experience with SQL, MySQL, or PostgreSQL. Knowledge of Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn. Experience with Machine Learning algorithms such as Linear Regression, Logistic Regression, Decision Trees, Random Forest, SVM, KNN, and XGBoost. Strong understanding of Statistics, Probability, Hypothesis Testing, and Predictive Modeling. Experience in Exploratory Data Analysis (EDA), Data Cleaning, and Feature Engineering. Knowledge of Deep Learning frameworks such as TensorFlow, PyTorch, or Keras. Experience with data visualization tools such as Power BI, Tableau, or Looker. Knowledge of NLP, Generative AI, and Large Language Models (LLMs). Familiarity with cloud platforms such as AWS, Azure, or Google Cloud. Knowledge of MLOps, Docker, Git, and model deployment. Strong analytical, problem-solving, and communication skills. Ability to translate complex data findings into actionable business recommendations.

What you’ll do

Collect, clean, process, and analyze datasets; develop, evaluate, deploy, and monitor machine learning and statistical models to address business problems. Communicate findings through dashboards, reports, and documentation, and collaborate with analysts, engineers, and stakeholders.

Requirements

The posting seeks programming experience in Python or R, SQL knowledge, and familiarity with data analysis, statistics, machine learning algorithms, and model evaluation. It also lists preferred knowledge of deep learning, visualization tools, NLP and generative AI, cloud platforms, MLOps, Docker, and Git, along with analytical, problem-solving, and communication skills.

Listed skills

• Python · Preferred
• SQL · Preferred
• Machine learning · Preferred
• Data visualization · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• R
• SQL
• Machine Learning
• Exploratory Data Analysis
• Data Cleaning
• Feature Engineering
• Statistical Modeling
• Predictive Modeling
• Statistics
• Data Visualization
• Deep Learning
• Natural Language Processing
• Generative AI
• MLOps
• Model Deployment

Job areas

• Data & Analytics
• Technology
• Software
• Science & Research

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