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Experienced Full Stack Data Entry Specialist – Remote Data Science and Analytics

Remote · Germany Full-time

At careerzynith, we're on a mission to revolutionize the way we approach data-driven decision making. As a leading healthcare and retail company, we're committed to creating more joyful lives through better health. We're now seeking an experienced Full Stack Data Entry Specialist to join our team of talented professionals in a remote capacity. This is an exciting opportunity to leverage your skills and expertise to drive business growth and success.

About careerzynith

careerzynith is a global healthcare, pharmacy, and retail leader with a 170-year history of caring for communities. Our mission is to create more joyful lives through better health. We operate almost 9,000 retail locations across the United States, Puerto Rico, and the U.S. Virgin Islands, serving over 10 million customers every day. Our pharmacists play a vital role in the U.S. healthcare system by providing a wide range of pharmacy and healthcare services, including those that promote equitable access to care for the nation's medically underserved populations.

Job Responsibilities

As a Full Stack Data Entry Specialist, you will be responsible for:

  • Building models and tools using technical expertise in machine learning, statistical modeling, probability and decision theory, and other quantitative methods. Innovate by adapting to new modeling techniques and procedures.
  • Understanding the business context behind large datasets and developing significant analytical solutions.
  • Applying analytical rigor and statistical techniques to analyze large datasets, using advanced statistical methods including predictive statistical models, customer profiling, segmentation analysis, survey design, analysis, and data mining. Develop recommendations and optimization algorithmic designs, perform data retrieval, complexity analysis, and clinical computing.
  • Programming using a tech stack including Python, PySpark, Matplotlib, TensorFlow, PyTorch, etc.
  • Performing machine learning strategies, and supervised and unsupervised algorithms to build predictive models and prescriptive solutions to support various business use cases.
  • Building algorithms like decision trees, regression, XGBoost, K means, and anomaly detection. Interpretable ML, Bayesian theory, etc.
  • Utilizing Cloud Computing on Azure/Databricks, querying in Snowflake.
  • Utilizing software tools and methodologies including GitHub, Continuous integration and delivery, agile methodologies.
  • Collaborating with finance, researchers, software developers, and business leaders to define product requirements and provide analytical support.
  • Communicating verbally and in writing to business clients and management teams with varying levels of technical expertise, educating them about our systems, as well as sharing insights and recommendations.

Essential Qualifications

* Bachelor's degree and a minimum of 4 years of experience in data science, machine learning, quantitative or computational skills OR High School/GED and a minimum of 7 years of experience in data science, machine learning, quantitative or computational skills.

  • M.S. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar.
  • At least 4 years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
  • Advanced experience in SQL, Python, PySpark or other languages.
  • Advanced degree skills in exploratory data analysis, feature engineering and selection, detecting patterns, learning distributions, visualizing results, and extracting insights to support businesses in making informed data-driven decisions.
  • Experience using decision trees, and building classifiers.
  • Experience with supervised machine learning techniques (linear and logistic regression, time series modeling, generalized linear models, decision trees, support vector machines, etc.) and unsupervised machine learning techniques (K means, hierarchical clustering, association rules, principal components).
  • Experience with Cloud ML systems, distributed computing, data pipelines, cloud data stores, and serving engines.
  • Experience designing and analyzing A/B experiments.
  • Advanced degree skills in conveying rigorous technical standards and issues to non-experts.
  • Experience working in dynamic environments and working with ambiguity, prioritizing needs, and delivering results.
  • Experience efficiently communicating technical solutions and advocating to data scientists, engineering teams, and business audiences.
  • At least 2 years of experience contributing to business decisions in the workplace.
  • At least 2 years of direct management, indirect management, and/or cross-functional team management.
  • Willing to travel up to/at least 10% of the time for business purposes (within the country and out of the country).

Preferred Qualifications

* Ph.D. in STEM, PC science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar.

  • Experience working with IoT, and Edge AI is a plus.
  • Experience in Reinforcement Learning is a plus.
  • Experience in Healthcare is a plus.

Benefits

* Company-Paid Life Insurance

  • Medical, Prescription Drugs, Dental, and Vision
  • Retirement Savings Plan – 401(k)
  • Employee Stock Purchase Plan
  • Paid Time Off (PTO)
  • Holidays
  • Paid Parental Leave (PPL)
  • Transportation Benefit Plan
  • Employee Store Discount
  • Voluntary Life & Personal Accident Insurance

Why Join careerzynith?

At careerzynith, we're committed to creating a workplace culture that values diversity, equity, and inclusion. We believe that our differences are what make us stronger, and we strive to create an environment where everyone feels welcome, respected, and empowered to succeed. We offer a range of benefits and programs to support our employees' physical, emotional, and financial well-being, including:

  • Competitive salaries and bonuses
  • Comprehensive health insurance and wellness programs
  • Retirement savings plans and employee stock purchase plans
  • Paid time off and holidays
  • Professional development opportunities and training programs
  • A dynamic and inclusive work environment

How to Apply

If you're a motivated and talented individual who is passionate about data science and analytics, we encourage you to apply for this exciting opportunity. Please submit your application through our website, including your resume, cover letter, and any relevant work samples or projects. We can't wait to hear from you! Apply for this job

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