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Violet Stars

Data Scientist

Position Overview

We are seeking a Data Scientist to join our AI/ML team and contribute to the development of advanced data-driven solutions. The ideal candidate will be passionate about extracting actionable insights from large and complex datasets, building robust machine learning models, and solving real-world problems that directly impact our clients’ operations.

Key Responsibilities

  • Data Exploration & Analysis

    • Perform extensive data analysis on structured and unstructured datasets to identify trends, patterns, and anomalies that impact business operations.

    • Collaborate with domain experts and product teams to understand supply chain, healthcare, and other industry-specific challenges.

    • Develop statistical analyses and visualizations to uncover meaningful insights and drive decision-making.

  • Model Development & Deployment

    • Design, build, and validate machine learning models for tasks such as predictive analytics, anomaly detection, optimization, and classification.

    • Collaborate with engineering teams to deploy models into production environments, ensuring scalability, performance, and robustness.

    • Optimize and fine-tune models to improve accuracy, efficiency, and real-world applicability.

  • Feature Engineering & Data Pipelines

    • Develop efficient data pipelines for data ingestion, transformation, and feature extraction.

    • Work with big data platforms and tools like Spark, Hadoop, or Kafka to process and analyze large-scale datasets.

  • AI/ML Integration in NexusAI

    • Contribute to NexusAI’s Digital Twin Environment by building models that simulate and predict real-time outcomes in supply chain and healthcare operations.

    • Leverage real-time anomaly detection and forecasting techniques to proactively identify risks and recommend solutions.

  • Collaboration & Communication

    • Work cross-functionally with engineers, product managers, and DevOps teams to align data science solutions with business goals and client needs.

    • Present findings, results, and recommendations to technical and non-technical stakeholders through clear and compelling data storytelling.

  • Continuous Learning & Innovation

    • Stay current with advancements in AI/ML techniques, tools, and frameworks, incorporating innovative approaches into NexusAI.

    • Experiment with emerging methods such as reinforcement learning, natural language processing (NLP), or time series forecasting to solve complex problems.

Qualifications

Why Join NexStratus?

  • Gain hands-on experience in consulting with exposure to diverse projects and clients.

  • Be part of a forward-thinking team that values creativity, collaboration, and continuous improvement.

  • Enjoy opportunities for career advancement and professional growth in a fast-paced industry.

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How to Apply?

Interested candidates are invited to submit their resume and a cover letter detailing their experience and why they are the ideal fit for this role to learnmore@nexstratus.com.

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NexStratus is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

 Required:

  • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

  • 3-5+ years of experience in data science roles, developing and deploying machine learning models.

  • Proficiency in Python or R, with hands-on experience using ML libraries/frameworks like Scikit-learn, TensorFlow, PyTorch, or XGBoost.

  • Strong understanding of machine learning algorithms (supervised, unsupervised, and time series) and statistical modeling techniques.

  • Experience working with large datasets, including data cleaning, transformation, and feature engineering.

  • Familiarity with SQL and NoSQL databases for querying and managing data.

  • Ability to build data pipelines and process large-scale data using big data tools like Spark or Hadoop.

  • Strong data visualization skills with tools such as Tableau, Power BI, or libraries like Matplotlib and Seaborn.


Preferred:

  • Experience with Digital Twins, simulation-based modeling, or supply chain optimization techniques.

  • Familiarity with real-time data processing tools and frameworks.

  • Knowledge of enterprise systems (TMS, WMS, ERP) or healthcare data standards (FHIR, HL7).

  • Experience with cloud platforms (AWS, Azure, or GCP) for model deployment and pipeline orchestration.

  • Understanding of NLP techniques for natural language interaction with data.

  • Strong communication skills, with the ability to present technical concepts to diverse audiences.

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