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Information Technology 🏢 Full Time ⭐️ Verified

Senior Data Scientist

Apex Data Innovations
San Francisco
Salary Estimate
USD 140.000 – USD 180.000
Latest
Live Update
31 Mei 2026
Deadline
1 Jun 2027

Job Description

Join the Future of Analytics

We are Apex Data Innovations, a leading tech firm at the forefront of predictive analytics and artificial intelligence. We are seeking a visionary Senior Data Scientist to join our elite San Francisco team. In this role, you will not just analyze data; you will architect the solutions that drive our core product strategy and redefine user engagement.

Your Mission

As a Senior Data Scientist at Apex, you will bridge the gap between complex statistical modeling and real-world business application. You will lead high-impact projects, mentor junior data scientists, and collaborate directly with cross-functional product teams to turn raw data into actionable insights.

Key Responsibilities

  • Design, develop, and deploy scalable machine learning models and statistical algorithms to solve complex business problems.
  • Perform exploratory data analysis (EDA) and build predictive models to optimize business processes and revenue streams.
  • Collaborate with engineering teams to integrate models into production environments using cloud infrastructure (AWS/Azure).
  • Communicate complex findings and model performance metrics to stakeholders through clear, compelling visualizations and presentations.
  • Conduct A/B testing and experimental design to validate product changes and drive data-informed decision-making.
  • Stay abreast of the latest research in Deep Learning and Natural Language Processing to innovate our product offerings.
  • Oversee the data pipeline architecture to ensure data quality, integrity, and availability.

Qualifications

  • Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in data science, machine learning, or a similar analytical role.
  • Expert proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
  • Strong experience with deep learning frameworks such as TensorFlow or PyTorch.
  • Proven track record of deploying models to production and working with big data technologies (Spark, Hadoop).
  • Excellent communication skills with the ability to translate technical jargon into business value.
  • Experience in a fast-paced, agile startup environment is highly preferred.

Responsibilities

  • Design, develop, and deploy scalable machine learning models and statistical algorithms to solve complex business problems.
  • Perform exploratory data analysis (EDA) and build predictive models to optimize business processes and revenue streams.
  • Collaborate with engineering teams to integrate models into production environments using cloud infrastructure (AWS/Azure).
  • Communicate complex findings and model performance metrics to stakeholders through clear, compelling visualizations and presentations.
  • Conduct A/B testing and experimental design to validate product changes and drive data-informed decision-making.
  • Stay abreast of the latest research in Deep Learning and Natural Language Processing to innovate our product offerings.
  • Oversee the data pipeline architecture to ensure data quality, integrity, and availability.

Qualifications

  • Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in data science, machine learning, or a similar analytical role.
  • Expert proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
  • Strong experience with deep learning frameworks such as TensorFlow or PyTorch.
  • Proven track record of deploying models to production and working with big data technologies (Spark, Hadoop).
  • Excellent communication skills with the ability to translate technical jargon into business value.
  • Experience in a fast-paced, agile startup environment is highly preferred.

Required Skills

Python Machine Learning SQL TensorFlow PyTorch A/B Testing Statistical Analysis Data Visualization Big Data Cloud Computing Deep Learning AWS Agile

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