Data Scientist (Freelancer)

Soul Ai; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Soul Ai seeks top-tier Data Scientists to design, develop, and deploy scalable data science solutions for large datasets. You will architect advanced ML models (deep learning, RL, ensemble) and apply rigorous statistical analysis to derive business insights.

You will own end-to-end data science projects, from data acquisition and preprocessing to deployment and monitoring, and implement MLOps workflows including model training, versioning, and A/B testing to validate performance.

Qualifications

• Proficient in Python and R with ML modeling and statistical analysis.
• Strong experience building scalable data pipelines and ML models.
• Experience with MLOps, model deployment, monitoring, and A/B testing.
• Familiar with data privacy regulations and ethical AI practices.

Responsibilities

• Lead design, development, and deployment of scalable data science solutions.
• Architect advanced ML models and apply statistical analysis for insights.
• Own full lifecycle of data science projects from data to deployment and monitoring.
• Implement MLOps workflows and conduct A/B testing to validate models.

Skills

Python

R

ML modeling

Statistical analysis

A/B testing

Data visualization

Big data pipelines

Cloud platforms

MLOps

NLP/Computer vision (Nice to have)

Ethical AI / privacy

Tools

Pandas/NumPy/Scikit-learn

Apache Spark/Dask

AWS/GCP/Azure

Docker/Kubernetes

MLflow/CI-CD

Tableau/Plotly Dash

Job description

We are looking for top-tier Data Scientists with expertise in predictive modeling, statistical analysis, and A/B testing. If you have experience in this field then this is your chance to collaborate with industry leaders.

Responsibilities

• Lead design, development, and deployment of scalable data science solutions optimizing large-scale data pipelines in collaboration with engineering teams.
• Architect advanced machine learning models (deep learning, RL, ensemble) and apply statistical analysis for business insights.
• Apply statistical analysis, predictive modeling, and optimization techniques to derive actionable business insights.
• Own the full lifecycle of data science projects"from data acquisition, preprocessing, and exploratory data analysis (EDA) to model development, deployment, and monitoring.
• Implement MLOps workflows (model training, deployment, versioning, monitoring) and conduct A/B testing to validate models.

Required Skills

• Expert in Python, data science libraries (Pandas, NumPy, Scikit-learn), and R with extensive experience with machine learning (XGBoost, PyTorch, TensorFlow) and statistical modeling.
• Proficient in building scalable data pipelines (Apache Spark, Dask) and cloud platforms (AWS, GCP, Azure).
• Expertise in MLOps (Docker, Kubernetes, MLflow, CI/CD) along with strong data visualization skills (Tableau, Plotly Dash) and business acumen.
• Nice to Have: Experience with NLP, computer vision, recommendation systems, or real-time data processing (Kafka, Flink).
• Knowledge of data privacy regulations (GDPR, CCPA) and ethical AI practices.
• Contributions to open-source projects or published research.