Data Scientist

Data Scientist
Experience –7+ years
 7 years of experience in data science, analytics, machine learning, or a related field, including hands-on experience delivering models and analytics solutions to production.

Job Summary
We are seeking a Data Scientist to turn complex data into actionable insights and machine learning solutions that drive business value. The successful candidate will work with product managers, engineers, analysts, and business stakeholders to define problems, design experiments, build models, and deliver data-driven recommendations.

The role covers exploratory data analysis, statistical modeling, machine learning, A/B testing, and clear communication of results to both technical and non-technical audiences.

Key Responsibilities
Understand business problems and translate them into analytical and modeling tasks.
Perform exploratory data analysis to uncover patterns, trends, and anomalies.
Design and analyze experiments, including A/B tests and multivariate tests.
Build, evaluate, and deploy predictive models and machine learning solutions.
Develop features, select algorithms, tune models, and validate performance.
Create dashboards, reports, and visualizations to communicate insights.
Collaborate with data engineers to ensure reliable, scalable data pipelines.
Work with engineering teams to integrate models into production systems.
Monitor model performance, data quality, and drift over time.
Document methodologies, assumptions, results, and recommendations.
Present findings and recommendations to business and technical stakeholders.
Mentor junior analysts or data scientists on methodology and best practices.
Required Qualifications
7+ years of experience in data science, analytics, machine learning, statistics, or a related field.
Strong programming skills in Python or R; Python is preferred.
Solid knowledge of statistics, experimental design, and hypothesis testing.
Experience with machine learning algorithms for classification, regression, clustering, and time series.
Proficiency with libraries such as scikit-learn, pandas, NumPy, and matplotlib/seaborn.
Experience with SQL and relational databases.
Familiarity with data visualization tools such as Tableau, Power BI, or similar.
Experience building and deploying models in a production environment.
Understanding of A/B testing, causal inference, and evaluation metrics.
Strong communication skills and ability to explain technical results to non-technical audiences.
Good problem-solving, prioritization, and collaboration skills.
Preferred Qualifications
Experience with deep learning frameworks such as TensorFlow or PyTorch.
Familiarity with big data tools such as Spark, Hadoop, or cloud data platforms.
Hands-on experience with cloud ML services such as AWS SageMaker, GCP Vertex AI, or Azure Machine Learning.
Knowledge of MLOps practices, including model versioning, CI/CD for ML, and monitoring.
Experience with NLP, recommendation systems, or forecasting.
Familiarity with Git, code review, and software engineering best practices.
Experience working in an Agile or Scrum environment.
A bachelor’s or master’s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.
Typical Technology Stack
Languages: Python, SQL; R is a plus.
Data manipulation and analysis: pandas, NumPy, SciPy.
Machine learning: scikit-learn, XGBoost, LightGBM, CatBoost.
Deep learning (optional): TensorFlow, PyTorch, Keras.
Visualization: matplotlib, seaborn, Plotly, Tableau, Power BI.
Data platforms: PostgreSQL, MySQL, Snowflake, BigQuery, Redshift.
Big data (optional): Spark, Hadoop.
Cloud: AWS, Azure, or GCP.
MLOps (optional): MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML.
Development: Git, Jupyter, VS Code, CI/CD pipelines.

#Only on w2

Preferred Visa: OPT,GCEAD,GC,USC,H4EAD

Interested candidates share with me your resumes to meher@sunixasolutions.com