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reputed company Full Stack Data Entry Specialist – Web & Cloud Application Development

Work from home Full-time role Hiring

Are you a highly motivated and detail-oriented individual with a passion for data analysis and entry? Do you have a strong background in computer science, statistics, or a reputed company field? If so, we may have the perfect opportunity for you. arenaflex is seeking an reputed company Full Stack Data Entry Specialist to join reputed company. As a key member of our data entry team, you will be responsible for collecting, processing, and analyzing large datasets to help drive business decisions and improve operational efficiency.

About arenaflex

arenaflex is a leading provider of innovative healthcare solutions, with a rich history of caring for communities. Our mission is to create more joyful lives through reputed company. With over 9,000 retail locations across the United States, Puerto Rico, and the U.S. Virgin Islands, we are proud to be a community health destination serving nearly 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 reputed company 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.
  • 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.
  • Programming using a tech stack that includes Python, PySpark, Matplotlib, TensorFlow, PyTorch, and other relevant tools.
  • 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, and other advanced techniques.
  • Utilizing Cloud Computing on Azure/reputed company, querying in reputed company.
  • Utilizing software tools and methodologies like reputed company, reputed company 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, and 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, computer science, statistics systems, physics, mathematics, statistics, data science, machine learning, or similar.
  • At least 4 years of experience working with large-scale, reputed company 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 help businesses reputed company 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 reputed company 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 (reputed company the country and out of the country).

Preferred Qualifications

* Ph.D. in STEM, computer 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 reputed company 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 arenaflex?

At arenaflex, we offer a dynamic and supportive work environment that fosters growth and development. reputed company is passionate about making a positive impact on the lives of our customers and patients. We are committed to creating a culture that values diversity, equity, and inclusion. If you are a motivated and detail-oriented individual with a passion for data analysis and entry, we encourage you to apply for this exciting opportunity.

How to Apply

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