- We are seeking a highly skilled Data Scientist with expertise in statistics, time series analysis, and NLP to join our dynamic team.

- The ideal candidate will have a strong background in advanced statistical techniques, machine learning algorithms, and data-driven forecasting.

- This role involves identifying patterns, trends, and anomalies in complex datasets and applying statistical modeling to solve business challenges and drive innovation.

Key Responsibilities :

- Apply advanced statistical methods to analyze large and complex datasets and extract meaningful insights.

- Design and implement time series analysis techniques for forecasting and trend detection, leveraging models such as ARIMA, SARIMA.

- Develop, test, and deploy machine learning models for pattern detection, anomaly identification, and predictive analytics.

- Create scalable forecasting models to address real-world business problems across various domains.

- Perform hypothesis testing and statistical validation to ensure reliability and accuracy of findings.

- Clean, preprocess, and validate data to improve its usability and integrity for analysis.

- Visualize and interpret analytical findings to communicate actionable insights to non-technical stakeholders effectively.

- Collaborate with cross-functional teams to implement data-driven solutions tailored to business challenges.

- Continuously research and implement the latest advancements in statistics, AI, and time series modeling to enhance analytics capabilities.

Required Qualifications :

- Bachelors or Masters degree in Statistics, Applied Mathematics, or a related quantitative field.

- 4 years of experience in data science, with a strong focus on statistical analysis, time series modeling, and NLP.

- Expertise in time series analysis, including ARIMA, SARIMA, Holt-Winters, and other forecasting techniques.

- Proficiency in programming languages like Python, R, or similar, with experience using libraries such as statsmodels, Prophet, Scikit-Learn, and NumPy.

- Strong understanding of statistical concepts, including regression analysis, Bayesian methods, and hypothesis testing.

- Experience with data visualization tools such as Tableau, PowerBI, Matplotlib, or Seaborn for presenting insights.

- Hands-on experience with data manipulation tools such as SQL, Pandas, and Excel.

- Excellent problem-solving and critical-thinking skills, with the ability to simplify complex statistical concepts for non-technical audiences.