96 KiB
Machine Learning Engineer / Data Scientist
Apple
San Diego, CA
As a Machine Learning Engineer / Data Scientist within the Ground Truth Systems Team, you will be part of a team building infrastructure and tools for exciting new technologies that will shape our future. We build web services that work at scale to support new products and also enable Machine Learning development workflows. We are looking for a Machine learning (ML) engineer with a broad experience and knowledge in machine/deep learning and computer vision. You will be part of every stage of development from concept to deployment. The Engineer will be working on cutting edge problems in efficient data annotation building ML models that assist humans in reducing labeling efforts without sacrificing quality.
Data Scientist
TikTok
Mountain View, CA
Develop comprehensive product metrics and quantitative measurement structure based on product stages and business purposes.
Implement standardized product reports, ad hoc queries, and data related projects
Design and implement reporting dashboards and the associated data pipeline to deliver insights and improve the workflows of internal teams
Partner closely with key stakeholders to optimize overall product adoption and performance driven growth. Provide suggestions for improvements to align with the business goal
Measure and visualize the effectiveness of product updates, conduct research and analysis on various business processes to identify business problems, and further provide optimization suggestions to improve operating efficiency
Data Scientist, Analytics
Los Angeles, CA
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
- Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.link
Data Scientist
Amazon
Nowy Jork, NY
- Design, build and automate datasets to scale and support business needs, allowing you to focus on answering hard and ambiguous question
- Identify, develop, manage, and execute research to uncover areas of opportunity and present recommendations that will shape the future of the retail website
- Collaborate with Qualitative Researchers on an iterative approach to a deep understanding of our customers and their behaviors
- Retrieve and analyze data using a broad set of Amazon’s data technologies and resources, knowing how, when, and which to use.
- Collaborate with product, technical, business, marketing, finance, and UX leaders to gather data and metrics requirements.
- Design, drive and analyze experiments to form actionable recommendations. Present recommendations to business leaders and drive decisions.
- Manage and execute entire projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
- Develop and document scientific research to be shared with the greater data science community at Amazon
Data Scientist, Engineering
Nowy Jork, NY
As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user.
Data scientist -Remote
Starbucks
Seattle, WA
Extract and transform data from multiple sources in preparation for exploratory data analysis, modeling, and reporting.
Leverage predictive and inferential advanced statistical and machine learning techniques to solve business problems, including methods to surface uncertainty intervals to provide increased context.
Transform model outputs into formats that are digestible to the end users through visualization, clear tables, and/or thoughtful presentations. Assist technical and non-technical end users in how to leverage and interpret the analysis.
Drive innovation by proposing and testing novel techniques and technologies to solve known problems and identify new business problems that can be addressed using data science products developed by the team.
Data Scientist - Instagram, Core Growth
Menlo Park, CA
Help Instagram acquire our next wave of new users and tap into new markets and demographics. Enable Instagram to grow in a way that is incremental to the Family of Apps and expand our footprint, while maintaining a differentiated experience for our users. Have a solid understanding of emerging market growth and ensure that Instagram breaks into new territories, and better understand how users in emerging markets use Instagram differently.
import pandas as pd
df = pd.read_csv('skill.csv')
df| skill | sum | |
|---|---|---|
| 0 | Python | 6 |
| 1 | SQL | 5 |
| 2 | Communication and collaboration skills | 5 |
| 3 | Statistical/mathematical software (e.g. R, Sta... | 5 |
| 4 | Master’s degree + | 4 |
| 5 | Bachelor's degree + | 3 |
| 6 | Ph.D. | 3 |
| 7 | Experience with large datasets | 2 |
| 8 | Experience in business analysis | 2 |
| 9 | Experience in data analysis | 2 |
| 10 | Experience in product analysis | 2 |
| 11 | Experience in analytics | 2 |
| 12 | Counterfactual causal models | 1 |
| 13 | Advanced competency in working with time serie... | 1 |
| 14 | sampling methods | 1 |
| 15 | Synthetic control models | 1 |
| 16 | Matching approaches | 1 |
| 17 | Deep knowledge of traditional ML concepts | 1 |
| 18 | Experience initiating and driving projects | 1 |
| 19 | Stochastic models | 1 |
| 20 | Multivariate analysis | 1 |
| 21 | Experience working in data science in e-commerce | 1 |
| 22 | Recommendation systems | 1 |
| 23 | Information retrieval | 1 |
| 24 | NLP | 1 |
| 25 | Demand modeling | 1 |
| 26 | Financial analysis | 1 |
| 27 | Keras | 1 |
| 28 | Understanding of algorithms | 1 |
| 29 | Research science | 1 |
| 30 | Understanding of data structures | 1 |
| 31 | Ability to succeed in an innovative and fast-p... | 2 |
| 32 | Leadership skills | 1 |
| 33 | Numpy | 1 |
| 34 | Scipy | 1 |
| 35 | Statistical analysis | 1 |
| 36 | PyTorch | 1 |
| 37 | Tensorflow | 1 |
| 38 | Previous publication in conferences | 1 |
| 39 | Regression modeling | 1 |
| 40 | Data modeling | 1 |
| 41 | Machine learning | 1 |
| 42 | Understanding of software design principles | 1 |
import matplotlib.pyplot as plt
import numpy as np
df = df.sort_values(by=['sum'])
ypos = np.arange(len(df.skill))
fig = plt.figure(figsize=(10,10))
ax = fig.add_axes([0,0,1,1])
ax.barh(df['skill'],df['sum'])
plt.show()
