Job Description

Overview of the Job:

The Data Scientist will create prediction models, support corporate objectives, and extract insights from complicated datasets using cutting-edge statistical and machine learning approaches. In a cooperative, creative setting, you will work directly with product, engineering, and stakeholder teams to convert raw data into actionable intelligence and contribute to AI-driven solutions.

Principal Duties:

Gather, clean, and preprocess sizable datasets from various sources with the use of ETL pipelines, Python, and SQL.

Utilizing frameworks like scikit-learn, TensorFlow, or PyTorch, create and implement machine learning models for anomaly detection, categorization, and forecasting.

To convey findings, use exploratory data analysis (EDA) and produce visualizations using Tableau, Power BI, or Matplotlib.

- Establish measurements, conduct A/B testing on hypotheses, and refine algorithms for production in conjunction with cross-functional teams.

- Keep up with the latest developments in big data and AI/ML technologies and incorporate them into scalable solutions.

Methodologies are documented, reports are produced, and non-technical stakeholders are given insights.

Assure ethical AI techniques and compliance with data protection laws (such as the CCPA and GDPR).

Ability:

Proficiency in Python, R, or Julia, as well as familiarity with ML frameworks and data manipulation tools like NumPy and Pandas.

Strong background in probability, statistics, and algorithms; familiarity with both supervised and unsupervised learning.

Proficiency in big data tools like Hadoop and Spark, as well as SQL and NoSQL database queries.

Proficiency in data visualization and narrative techniques to effectively communicate intricate outcomes.

The ability to solve problems with an emphasis on practical applications.

It helps to be familiar with version control (Git) and cloud platforms (AWS, Azure, GCP).

Outstanding communication and teamwork abilities in hectic situations.

Experience and Education:

A bachelor's degree in mathematics, statistics, computer science, or a similar discipline is required; a master's or doctoral degree is recommended.

Three or more years of work experience in analytics, data science, or a related field, preferably in technology or finance.

Projects or publications that showcase data modeling and analysis.

Work authorization in the USA is necessary; there is no sponsorship for a visa.

Annual Salary:

$110,000 to $150,000 base pay, depending on competence, location in the United States, and experience. By offering competitive compensation, we hope to draw in and keep outstanding individuals.

Pay and Benefits:

Up to 12% of base pay, contingent on both individual and group performance.

RSUs or stock options for long-term growth involvement.

All-inclusive health, dental, and vision plans with affordable premiums from the start.

- 401(k) with an employer match of up to 5%.

Eleven paid holidays, eighteen paid days off, and an unlimited number of mental health days.

Budget each year for conventions, certifications (like AWS ML), and courses.

Parental leave, wellness stipends, and flexible remote/hybrid work for employees in the United States.

- Employee discount programs, transit benefits, and home office setup allowance.

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