Data Scientist (Time Series Forecasting) - US based AI Solution firm - Remote - Immediate Joiner

datavruti; India; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

datavruti is seeking a Data Scientist for its AI-first data solutions practice. The role requires 5–7 years of hands-on experience in machine learning, statistics, forecasting, and predictive analytics, with the ability to develop end-to-end ML solutions from data ingestion to deployment.

The successful candidate will design and deploy ML models (logistic regression, trees, SVMs, clustering), work with large datasets, perform EDA, feature engineering, and collaborate with cross-functional teams

Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
• 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.

Responsibilities

• Design, develop, and deploy ML models for business-critical use cases.
• Build and optimize traditional ML models (Logistic Regression, Decision Trees, Support Vector Machines, Clustering).
• Develop forecasting solutions using ARIMA / SARIMA and Exponential Smoothing.
• Perform exploratory data analysis (EDA), feature engineering, and data validation.
• Evaluate model performance using appropriate statistical and business metrics.
• Collaborate with business stakeholders to translate requirements into analytical solutions.
• Build scalable data pipelines and support model deployment in production environments.
• Monitor model performance, identify data drift, and implement retraining strategies.
• Present insights and recommendations to technical and non-technical stakeholders.

Job description

Hiring for: A US-based, AI-first data solutions company founded by seasoned technology leaders.

Role: Data Scientist

Positions: 4

Experience: 5 to 7 years

Type: On-site / Permanent

Salary: Up to INR 20 LPA (Based on fitment)

Notice Period: Immediate to 15-20 Days

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Traditional Statistical Modelling, Forecasting, and Predictive Analytics. The ideal candidate will have hands-on experience building and deploying end-to-end ML solutions, working with large datasets, and translating business problems into scalable data science solutions.

The role requires a strong foundation in statistics, predictive modelling, feature engineering, model evaluation, and time-series forecasting, along with the ability to collaborate with cross-functional teams to deliver business impact.

Key Responsibilities

• Design, develop, and deploy Machine Learning models for business-critical use cases.
• Build and optimize traditional ML models such as:
• Logistic Regression
• Decision Trees
• Support Vector Machines
• Clustering Algorithms
• Develop forecasting solutions using:
• ARIMA / SARIMA
• Exponential Smoothing
• Perform exploratory data analysis (EDA), feature engineering, and data validation.
• Evaluate model performance using appropriate statistical and business metrics.
• Work with structured and semi-structured datasets from multiple sources.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Build scalable data pipelines and support model deployment in production environments.
• Monitor model performance, identify data drift, and implement model retraining strategies.
• Present insights and recommendations to technical and non-technical stakeholders.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related quantitative field.
• 5+ years of hands-on experience in Data Science, Machine Learning, and Forecasting.

Technical Skills

• Strong understanding of supervised and unsupervised learning algorithms.
• Experience with ensemble methods and advanced ML techniques.
• Expertise in model selection, hyperparameter tuning, and performance optimization.

Forecasting & Statistics

• Strong understanding of:
• Time-Series Analysis
• Statistical Inference
• Hypothesis Testing
• Probability Distributions
• A/B Testing

Programming

• Advanced proficiency in Python.
• Experience with:
• NumPy
• Scikit-learn
• XGBoost / LightGBM

Data & SQL

• Strong SQL skills with experience in complex queries and performance optimization.
• Experience working with large-scale datasets.
• Experience with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.
• Exposure to AWS, Azure, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and ML model deployment practices.
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Strong business acumen and data-driven decision-making mindset.