Data Scientist | Machine Learning | AI & Advanced Analytics | Data-Driven Decision Making
We are looking for an innovative, analytical, and results-oriented Data Scientist to join our growing team and support U.S.-based organizations across Technology, SaaS, Healthcare, Finance, Retail, Manufacturing, and Biotechnology industries.
This role is ideal for professionals who are passionate about transforming complex data into actionable insights, building predictive models, and leveraging Machine Learning and Artificial Intelligence to solve real-world business challenges. You'll collaborate with cross-functional teams to develop data-driven strategies that improve products, optimize operations, and drive business growth.
If you're excited about working with large datasets, advanced analytics, AI technologies, and cutting-edge data science tools, we'd love to hear from you.
What You'll Do
- Collect, clean, transform, and analyze structured and unstructured data from multiple sources.
- Develop predictive models, machine learning algorithms, and statistical analyses to solve business problems.
- Build, validate, and deploy machine learning models for production environments.
- Analyze customer behavior, business performance, operational efficiency, and market trends.
- Collaborate with Product, Engineering, Business Intelligence, Marketing, and Executive teams to translate business problems into analytical solutions.
- Design and maintain data pipelines, feature engineering processes, and model monitoring frameworks.
- Develop dashboards, reports, and visualizations to communicate complex insights to technical and non-technical stakeholders.
- Conduct A/B testing, hypothesis testing, forecasting, and statistical modeling.
- Optimize data quality, model performance, and automation processes.
- Stay current with emerging AI, Machine Learning, and Data Science technologies and best practices.
Data Science Expertise
- Data Science
- Machine Learning
- Predictive Analytics
- Statistical Modeling
- Data Mining
- Feature Engineering
- Forecasting
- Time Series Analysis
- A/B Testing
- Hypothesis Testing
- Data Visualization
- Business Analytics
- Natural Language Processing (NLP)
- Recommendation Systems
- Deep Learning
- AI Model Development
- Data Storytelling
- Model Deployment
- Model Monitoring
- Data-Driven Decision Making
Programming Languages & Technologies
Experience with one or more of the following:
- Python (Required)
- SQL (Required)
- R
- PySpark
- Scala
- Git
- Jupyter Notebook
- Google Colab
Machine Learning & AI
- Scikit-learn
- TensorFlow
- PyTorch
- XGBoost
- LightGBM
- OpenAI API
- LangChain
- Hugging Face
- MLflow
Cloud & Data Platforms
- AWS
- Microsoft Azure
- Google Cloud Platform (GCP)
- Databricks
- Snowflake
- BigQuery
- Redshift
- Azure Synapse
Visualization & BI
- Power BI
- Tableau
- Looker
- Matplotlib
- Seaborn
- Plotly
What We're Looking For
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field.
- 3+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
- Strong proficiency in Python and SQL.
- Experience building, validating, and deploying machine learning models.
- Strong knowledge of statistics, predictive modeling, and data analysis.
- Experience working with large datasets and cloud-based data platforms.
- Experience communicating technical findings to business stakeholders.
- Strong problem-solving, analytical thinking, and critical reasoning skills.
- Professional English proficiency (B2+/C1 preferred).
- Ability to work independently in a remote, multicultural environment.
Preferred Qualifications
- Master's degree in Data Science, Statistics, AI, Computer Science, or a related discipline.
- Experience supporting U.S.-based companies or global organizations.
- Experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI applications.
- Experience with MLOps, model deployment, and production environments.
- Knowledge of Docker, Kubernetes, CI/CD, and API development.
- Experience working in SaaS, Healthcare, Finance, Retail, or Biotechnology industries.
- AWS, Azure, GCP, Databricks, TensorFlow, or Microsoft certifications.
Why Join Us?
Join a forward-thinking organization where you'll help solve complex business challenges using data, artificial intelligence, and advanced analytics. You'll collaborate with world-class teams, influence strategic decisions, and build innovative solutions that create measurable business impact for U.S.-based organizations.
Next Step
Please remember to check your email and complete your One-Way Video Interview. This is the next step in our hiring process and will help us better understand your technical expertise, analytical thinking, problem-solving approach, and ability to transform data into business value. We look forward to learning more about you!
Requirements
Data Scientist – High Fit Resume Requirements
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field.
- 3+ years of experience as a Data Scientist, Machine Learning Engineer, or Advanced Analytics professional.
- Strong proficiency in Python and SQL.
- Experience building and deploying Machine Learning and Predictive Analytics models.
- Strong knowledge of Statistics, Hypothesis Testing, A/B Testing, and Statistical Modeling.
- Experience with Machine Learning libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
- Experience working with large datasets, data cleaning, feature engineering, and data visualization.
- Experience with Cloud Platforms (AWS, Azure, or Google Cloud).
- Experience using Power BI, Tableau, or Looker for data visualization and executive reporting.
- Professional English proficiency (B2+).
Preferred (Bonus)
- Master's degree in Data Science, AI, Statistics, or a related field.
- Experience supporting U.S.-based companies or global organizations.
- Experience with Generative AI, LLMs, OpenAI API, LangChain, Hugging Face, or RAG.
- Experience with Databricks, Snowflake, BigQuery, or Redshift.
- Knowledge of MLOps, Docker, Kubernetes, CI/CD, and model deployment.
- Experience in SaaS, Healthcare, Finance, Retail, Manufacturing, or Biotechnology.
- AI, Cloud, or Data Science certifications (AWS, Azure, Google Cloud, TensorFlow, Databricks, etc.).