NXT LABS - Senior Data Scientist

Client: NXT LABS

Contract: Freelance

Job Description

This is a remote position.

The role involves leading end-to-end data science projects, building predictive and statistical models, performing exploratory data analysis, designing data pipelines, and collaborating with various teams to drive business impact through data-driven insights. Responsibilities include developing dashboards, running A/B tests, ensuring data quality, and mentoring junior data scientists.

• Lead end-to-end data science projects from problem definition to deployment and business impact measurement.
• Build predictive models, statistical models, and machine learning solutions for business and product use cases.
• Perform exploratory data analysis to identify trends, patterns, and actionable insights.
• Design and implement data pipelines for large-scale structured and unstructured datasets.
• Develop and maintain data models, feature engineering pipelines, and experimentation frameworks.
• Work closely with engineering teams to deploy models into production environments.
• Build dashboards and reporting systems to communicate insights to stakeholders.
• Design and run A/B tests, hypothesis testing, and causal analysis to guide decision-making.
• Work with big data technologies to process and analyze large datasets efficiently.
• Ensure data quality, integrity, and governance across systems.
• Collaborate with product, engineering, and business teams to define metrics and success KPIs.
• Mentor junior data scientists and guide best practices in analytics and modeling.

Requirements

Technical Requirements

• 5–8+ years of experience in Data Science, Machine Learning, or Analytics roles.
• Strong programming skills in Python or R.
• Strong knowledge of SQL and relational databases (PostgreSQL, MySQL, etc.).
• Experience with machine learning libraries (Scikit-learn, XGBoost, TensorFlow, PyTorch, etc.).
• Strong foundation in statistics, probability, and linear algebra.
• Experience with data visualization tools (Tableau, Power BI, or similar).
• Experience working with large datasets and distributed systems (Spark, Hadoop, etc.).
• Understanding of data pipelines and ETL processes.
• Experience deploying models into production environments.

Nice to Have

• Experience with cloud platforms (AWS, GCP, Azure).
• Experience with real-time data processing systems.
• Familiarity with MLOps practices (model monitoring, CI/CD for ML).
• Experience with feature stores and data versioning systems.
• Knowledge of experimentation platforms and causal inference.
• Experience working in product-driven or high-growth environments.

Other Information

This position is fully remote, allowing flexibility in your work environment.