ECON 转 DS: job description 中找方向

水校ECON PhD有一颗想转DS的心。Applied micro，接触过教育和医疗相关的数据。为了准备毕业和找工作，现在想从LinkedIn中搜索相关的招聘信息来整理自己需要学习的东西。欢迎大家一起监督学习!

List 1: This one is quite overwhelming for a newbie. I use this for my long-term goal.

Tasks can include helping healthcare organizations sign up the right mix of physician specialties to serve the specific health care needs of a local community, developing a model to proactively identify students at risk of failing to graduate or meet required literacy standards, or using data to help fight the scourge of human trafficking; this just might be the role for you. (sounds like consulting in DS. probably needs a one-man team)

REQUIRED SKILLS:


Master’s or Doctoral Degree in Math, Statistics, Computer Science or related field


Knowledge required: Strong foundation in areas of statistics, mathematics, computer science, machine learning, and/or deep learning
 Skills required: Strong problem solving skills, quantitative/qualitative analysis skills


Abilities required: Ability to organize and prioritize work assignments to meet project needs


At least 5 years of experience in positions of increasing responsibility(no new grad), working with large datasets and conducting statistical and quantitative modeling, melding analytics with strong programming, data mining, clustering and segmentation 


Experience in client communications and relationship management; strong technical writing skills, strong verbal skills; and data visualization/presentation.
 Able to explain technology, techniques and approaches to others.


Strong data programming skills such as: SQL, Python, R, Hadoop, Hive, MapReduce, and/or other large data systems


Strong ability to rapidly prototype solutions to iteratively meet client needs
 Experience in cloud hosting technologies, such as AWS, ideally including AWS Redshift


Strong data visualization or storytelling skills, demonstrated ability to use data visualization tools such as Tableau (preferred) or other visualization technologies such as D3, Shiny, etc
Preference for domain expertise in healthcare preferred

List 2: recommendation system. marketing
Guide people toward behaviors beneficial to their health. 1) identify persona; 2) define objective; 3) engage using mass personalization; 4) achieve measurable outcomes; and 5) learn continuously, both the team and machine learning.

Position Summary
This position will be responsible for mining data (demographic, clinical, psychographic), developing statistical modeling, and contributing to machine learning platform.

Education & Experience

• Master’s Degree minimum with equivalent combination of education and experience
• Demonstrated analytical and data modeling capabilities
• Proficiency in SQL and R or Python
• Knowledge of basic statistical techniques and principles (frequentist and Bayesian)
• Experience in building machine learning models from messy data sources (cleaning, model selection, validation, etc.)
• Demonstrated ability to represent scientific findings and results to a scientific community
• Ability to effectively communicate complex, technical information to both technical and non-technical audience
• Experience with communicating to C-Level customers

List 3: Quality testing for maps.
The standard package: python or R + MapReduce
Not familiar with the goal though. The probability of getting routes wrong or getting ETA wrong?

As a Data Scientist within the Quality Testing and Statistics team, you are passionate about statistical sampling, quality measurement, and predictive models. You will work with map and location experts, engineering teams and fellow data scientists to develop testing plans, quality benchmarks, and predictive models to deliver analytic insights and solutions enabling the highest levels of quality throughout HERE’s offerings.
Develop sampling plans for data collection, quality evaluation, and the production of training data.
Design and create estimators and diagnostics for the evaluation of map quality along various use-cases.
Design and analyze A/B experiments that validate different optimization and solution approaches, and to calibrate model parameters.
Build and test analytic and statistical models to support improvement of a wide variety of data-driven processes for map-making data evaluation and decisions.
Develop code and outputs. Create summary results and provide interpretations to project leaders.
Provide support to the statistical and analytical needs of various departments within the company.
Who are you?
MS or PhD degree in Statistics, Mathematics, Econometrics, or related fields.
2+ years of related work experience.
Knowledge of sampling methods, and analytic methods such as regression, classifiers, clustering, association rules, decision trees, etc.
Proficiency with analysis and programming in R, or any similar package (Python, SAS, etc.).
Knowledge and experience with using GIS tools for spatial data analysis.
Knowledge of tools such as Pig, Hive, etc. for working with big data in Hadoop or Spark for data extraction/prep for analysis.
Application of statistics in quality area or Six Sigma will be a plus.
Excellent oral and written communication skills.




list 4: data analytics whose main job is probably writing up business reports in the energy industry.
Duties and Responsibilities
Use knowledge of utility data, organizations and priorities to advise clients on data-driven solutions to operational needs, regulatory mandates, and customer outreach
Leverage knowledge of the electricity and gas sector to select appropriate statistical and technical approaches to client challenges
Prepare reports, presentations, tools, and proposals explaining technical analytical methods and results to non-technical audiences
Project manage and/or support teams to deliver high quality analysis while remaining on time and on budget
Take initiative to validate and troubleshoot data and statistical models
Coach junior staff to develop their data science skills
Participate in meetings, conference calls, and email exchanges with clients
Track energy industry trends and emerging issues
Other duties as assigned.

Required Qualifications
.--Master’s Degree and 2-3 years of work experience in one of the following disciplines: data science, economics, statistics, public policy with a quantitative focus, or computer science. Experience, through coursework or work experience in the energy sector is highly preferred
Programming experience using R or Python building regression, classification, or other statistical models
Demonstrated interest in the energy industry via prior work experience, coursework, or side projects
Strong written and oral communication skills
Ability to multi-task and work independently in a fast-paced environment
Detail-oriented, especially when managing and analyzing large data sets
Must be able to travel locally and nationally up to approximately 30% of the time.

Preferred Qualifications
Project management experience, including supervising junior staff and tracking budgets and deliverables, preferably in a consulting or client-facing environment
Familiarity with Stata, SQL, or Julia or other numerical programming language
Coursework and/or practical experience in machine learning, applied econometrics and/or statistical program evaluation
Familiarity with the full data science stack, with a focus on visualization and data communication
Experience with model selection and validation methods
Real world experience scraping and/or munging large data sets.


list 5: similar to list 4.
What you’ll do:
Collaborate with engineering and product teams to add new features and contribute to the development of our data platform
Train customers on how to get the most out of their analytics
Support our sales team during customer calls and provide the data science "point of view" on how we help customers gain insights from their factory floor data.
Perform exploratory research on the latest methodologies in data science and predictive analytics, ranging from researching which algorithms may be useful to apply to manufacturing analytics to diving into the latest research on big data architectures
Consult with customers to clarify business problems and understand requirements, perform analysis and modeling, and develop visualizations to communicate your results.

Qualifications:
BS or MS in Computer Science, Computer Engineering, Electrical Engineering, Physics, Statistics or a related technical discipline
Understanding of statistics (e.g., hypothesis testing and regression models)
Experience with Python or other scripting languages (e.g. Perl)
Good communication skills, both for internal collaboration and working with clients
You love learning new technologies and like to tinker to understand how things work
You use a systematic problem-solving approach when facing challenging technical problems
Also helpful, but not required,
Previous internship or project experience with data science at scale, backend data analysis
Experience working with distributed computing tools (MapReduce, Hadoop, Hive, etc.)
Experience with packages such as NumPy, SciPy, pandas


list 6: market-segmentation. recommendation system.
What You Will Be Doing
Build and scale models to support audience segmentation.
Analyze Peta-Byte scale data sets in Video and TV audiences.
Coordinate and collaborate with engineering teams
What You Need for this Position
Ad Tech experience is a MUST
Python
R
SQL
Machine Learning
Julia
Big Pluses
Apache Spark
Experience with time series analysis such as ARIMA, LSTMs, Etc...

. 1point3acres.com
list 7: loT devices. Possible needs include ad-tech for business, market analysis for the product.
. 1point 3acres Required Skills & Experience
Expert level use of Python and/or R for Data science
Strong stats/math background
Genuine interest in IoT devices
Pydata is ideal (SciPy, Scikit Learn, Pandas, NumPy)
Comfortable working a cloud hosted environment
Excellent understanding of various machine learning methodologies

支持一个！~~~很用心

一起加油！！！！！！

Econ往偏marketing的DS方向很对口呀。比如advertising, customer analytics...都会用到很多计量模型
只是确实要补充一下硬技能让你获得动手能力：SQL, Python, R,Hadoop