Data Scientist - R01542454

Brillio; Bengaluru; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

A leading company in data solutions is seeking a Data Scientist with expertise in time series forecasting. The role involves developing forecasting models and utilizing machine learning techniques to support data-driven business decisions. Candidates should have a strong educational background and substantial experience in data science, with proficiency in Python and R. This opportunity offers a chance to make impactful contributions in a dynamic environment.

Qualifications

• 5-6 years of experience in data science focusing on time series forecasting.
• Strong proficiency in Python or R for data analysis and modeling.
• Excellent communication and presentation skills.

Responsibilities

• Develop and implement time series forecasting models.
• Analyze historical data patterns to identify key drivers.
• Collaborate with teams to ensure models align with business objectives.

Skills

Classification

Forecasting

Hypothesis Testing

Python/PySpark

Statistical analysis

Machine Learning

Data Analysis

Education

Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering

Tools

SQL

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Job description

Data Scientist

Primary Skills

• Classification (Decision Trees, SVM), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Great Expectation, Evidently AI, Hypothesis Testing, ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Probabilistic Graph Models, Python/PySpark, R/ R Studio, Regression (Linear, Logistic), SAS/SPSS, Statistical analysis and computing, Tools(KubeFlow, BentoML), T-Test, Z-Test

Specialization

• Data Science Advanced: Data Specialist

Job requirements

• Key Responsibilities: Develop and implement time series forecasting models to predict future trends, demand, and performance metrics. Leverage statistical methods, machine learning, and deep learning techniques for accurate forecasting. Work with large datasets from multiple sources and clean, process, and transform data for modeling purposes. Analyze historical data patterns and trends to identify key drivers of future outcomes. Perform data validation, anomaly detection, and ensure data integrity. Collaborate with business and technical teams to understand forecasting needs and ensure models align with business objectives. Communicate findings, insights, and predictions to both technical and non-technical stakeholders. Continuously optimize and improve forecasting models by experimenting with new algorithms, tools, and techniques. Use forecasting models to drive business decisions related to supply chain, demand planning, inventory, and more. Document processes, models, and code to ensure scalability and reproducibility. Key Requirements: Education: Bachelor's or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field. Experience: 5-6 years of experience in data science with a focus on time series forecasting. Proficiency in Python or R for data analysis and modeling. Strong knowledge of time series forecasting techniques such as ARIMA, SARIMA, ETS, Prophet, or LSTM. Experience with machine learning algorithms and statistical analysis. Familiarity with tools like SQL, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Experience working with large datasets and data pipelines in a cloud-based environment (AWS, Azure, or GCP). Strong problem-solving skills and the ability to interpret complex data. Excellent communication and presentation skills to translate complex data findings into actionable insights for business teams.