Job Title: Data Scientist
Location: Any
Job Type: Full-time

About Us
We are a specialized IT and AI software development company dedicated to transforming the educational landscape. We partner with higher education institutions and EdTech organizations in the USA to build cutting-edge, scalable AI and IT solutions. We pride ourselves on our Agile mindset, technical excellence, and commitment to delivering products that enhance educational outcomes and operational efficiency.

Role Summary
We are seeking a highly analytical and strategically minded Data Scientist (46 years experience) to drive our AI and data initiatives. In this role, you will apply advanced statistical and machine learning techniques to analyze complex business and educational data. Your primary focus will be to extract actionable insights and develop data-driven solutions that directly improve student learning outcomes and optimize the organizational strategies of our US higher education clients. Working closely with Product Owners, Data Engineers, and AI developers in an Agile setting, you will translate raw data into scalable solutions that propel academic and operational success.

Key Responsibilities
1. Statistical Modeling & Machine Learning

- Apply advanced statistical methods and machine learning techniques (e.g., regression, classification, clustering, time-series forecasting) to solve complex educational and business challenges.

- Design, build, and deploy predictive models focusing on student retention, enrollment forecasting, and personalized learning pathways.

2. Insight Extraction & Strategy Development





- Analyze vast amounts of structured and unstructured business data from various sources (Student Information Systems, Learning Management Systems, CRM platforms).

- Extract meaningful, actionable insights that help institutional leaders make informed, data-driven decisions to improve organizational strategies and operational scalability.

3. Improving Learning Outcomes

- Develop AI-driven algorithms and data solutions that identify at-risk students, recommend targeted interventions, and dynamically adapt course content to individual learning styles.

- Collaborate with educational experts to ensure data models accurately reflect and enhance pedagogical goals.

4. Data Storytelling & Visualization

- Translate complex statistical findings into clear, compelling narratives for non-technical stakeholders and university administrators.

- Work with UI/UX designers and engineers to help build intuitive data visualization dashboards that track institutional KPIs and student performance metrics.

5. Agile Collaboration & MLOps Integration

- Work within an Agile software development framework, actively participating in sprint planning, providing effort estimations, and delivering iterative value.

- Partner with Data Engineers to ensure data pipelines are optimized for ML workflows, and assist in transitioning experimental models into scalable, production-grade applications.

Required Qualifications

- Experience:



4 to 6 years of applied, hands-on experience in Data Science, applying statistical and machine learning techniques to real-world business problems.

- Programming & Tools: Expert-level proficiency in Python (Pandas, NumPy, Scikit-Learn) and SQL for complex data manipulation.

- Machine Learning: Deep understanding of applied statistics, probability theory, and machine learning algorithms. Experience with deep learning frameworks (TensorFlow, PyTorch) is highly desirable.

- Analytical Acumen: Proven track record of analyzing large-scale business data to extract insights that directly influence organizational strategy or product development.

- Communication: Exceptional verbal and written English skills. Ability to explain complex data science concepts and model metrics in terms of business value and educational impact.

- Methodology: Solid experience working in an Agile/Scrum environment alongside software engineering teams.

Preferred Qualifications

- EdTech Domain Knowledge: Prior experience working with Higher Education datasets, analyzing learning outcomes, or working with EdTech platforms (LMS, SIS).

- NLP & Generative AI: Familiarity with Natural Language Processing techniques and working with Large Language Models (LLMs) to analyze unstructured data (like student feedback or academic text).

- Cloud & Big Data: Experience deploying models in cloud environments (AWS, GCP, Azure) and working with modern data warehouses (e.g., Snowflake, BigQuery).

- Education: Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field

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