The dream career is one of the major tech firms for many aspiring data scientists.
吨他梦寐以求的职业是许多有抱负的数据科学家的主要高科技公司之一。
But you remove an overwhelming amount of cool jobs in other industries when you concentrate on the tech industry alone.
但是，当您仅专注于技术行业时，就可以消除其他行业中大量的酷工。
I’ve worked for a lot of different companies and I wouldn’t want to lose my experience. I worked on projects in the chemical industry in my former job. Before, I didn’t know the industry, and I was shocked at how advanced they are and the many insights I could gain, particularly IoT technology integration.
我曾在许多不同的公司工作过，我不想失去自己的经验。 我以前的工作是从事化工行业的项目。 以前，我对这个行业不了解，我对它们的先进程度以及我可以从中获得的很多见解感到震惊，尤其是物联网技术集成。
So, what are the reasons for searching for a position in a particular sector?
那么，寻找特定部门职位的原因是什么？
- You are working on exciting projects that relate to other technologies, such as genetics and IoT, 您正在从事与其他技术(例如遗传学和物联网)相关的令人兴奋的项目，
2. You deal with a large amount of data from various sources, such as computers, production processes, and wearables
2.您处理来自各种来源的大量数据，例如计算机，生产过程和可穿戴设备
3. You live in a region where no technology company is nearby.
3.您住在附近没有技术公司的地区。
4. You actually don’t like working in the tech sector
4.您实际上不喜欢在科技行业工作
5. You already have a different experience in the industry and you would like to contribute your expertise. In addition, an internal transfer is highly desirable as it enhances the potential to be employed because of the experience of the specialized sector.
5.您已经在该行业中拥有不同的经验，并且希望贡献您的专业知识。 另外，由于专业领域的经验，内部转让非常可取，因为它增加了被采用的潜力。
I give you five industries below to find exciting work positions outside the tech industry. I’m going to send you a brief overview of the industry, the wage level relative to the software industry, how recession-proof this industry is, project examples, and what data scientists’ skills the industry is looking for.
我为您提供以下五个行业，以查找技术行业以外令人兴奋的工作职位。 我将向您简要概述该行业，与软件行业相关的工资水平，该行业的经济衰退程度，项目示例以及该行业正在寻找的数据科学家的技能。
制药与生命科学
科 (Pharmaceuticals and Life Sciences
Branch)
COVID-19 forces us to keep hearing about vaccine production all the time. That shapes our perspective on this industry. But this is just one aspect of the sector as a whole.
COVID-19迫使我们一直保持有关疫苗生产的消息。 这塑造了我们对该行业的看法。 但这只是整个行业的一个方面。
The reality is, with many subsectors such as agricultural bioscience, diagnostics, therapeutics, pharmaceuticals, genomics and proteomics, veterinary life sciences, cosmetics, drug production, medical innovations, distribution, and many other services, the industry is broad and very heterogeneous.
现实是，农业生物科学，诊断学，治疗学，药物，基因组学和蛋白质组学，兽医生命科学，化妆品，药品生产，医疗创新，分销和许多其他服务等许多子行业，该行业是广泛的且非常不同。
In addition to vaccine production, we have other fields in the pharmaceutical field alone, such as antibody therapies, cell therapies, generic drugs, immunotherapy, proteins, or stem cells.
除了生产疫苗之外，我们还单独拥有制药领域的其他领域，例如抗体疗法，细胞疗法，非专利药，免疫疗法，蛋白质或干细胞。
The cost of creating new drugs starts from around a billion U.S. dollars today and goes up to two-digit billion U.S. dollars. The industry makes every attempt to minimize prices and make treatments available more quickly. That pushes for a comparable data-driven industry to the technology industry. To connect patients, service providers such as hospitals and physicians, and their own data together, all global players are building data ecosystems.
如今，开发新药的成本从十亿美元左右，到高达两位数的十亿美元。 该行业竭尽全力使价格降到最低，并更快地提供治疗。 这推动了与数据行业可比的技术驱动行业。 为了将患者，医院和医生等服务提供商以及他们自己的数据联系在一起，所有全球参与者都在建立数据生态系统。
I suggest you do some study on the various subsectors. When you see an offer for a job, always find out first about the subsector.
我建议您对各个子行业进行一些研究。 当您看到一份工作机会时，请务必先了解该子行业。
防衰退： (Recession-proof:)
Yeah, it is really recession-proof for the industry. Health care is still required, both for humans and for animals and pets. And the industry is also getting a boost in times like today.
是的，这对于行业而言确实是防衰退的。 仍然需要对人类以及动物和宠物进行保健。 像今天这样的时代，该行业也在得到发展。
项目： (projects:)
You can assume that as large as the number of subsectors, the variety of potential areas and projects is. Pages will fill up a detailed list of initiatives. So, I restrict it to three instances.
您可以假定，与子行业一样多，潜在领域和项目的多样性也是如此。 页面将填写计划的详细列表。 因此，我将其限制为三个实例。
Precision medicine: Medical therapies are increasingly focused on a patient’s unique, customized traits. These features are subtypes of illness, personal patient complications, health prognosis, and biomarkers of molecular and behavioral behavior. Any observable data point so that patients may be stratified, such as the score of disease severity, lifestyle attributes, or genomic properties, is a biomarker. The best care of a single patient is decided based on all of these results.
精密医学：药物治疗越来越关注患者的独特个性特征。 这些特征是疾病，个人患者并发症，健康预后以及分子和行为行为的生物标志物的亚型。 生物标记物是任何可观察到的数据点，以便可以对患者进行分层，例如疾病严重程度，生活方式属性或基因组特性得分。 基于所有这些结果，可以确定单个患者的最佳护理。
A true example is an ovarian cancer patient where chemotherapy was unsuccessful. So, to identify the misplaced nucleotide bases causing cancer, one conducted a genome sequencing. One noticed the modification among the 3 billion base pairs of a person with big data analytics (this corresponds to the number of words from 7798 Harry Potter’s The Philosopher’s Stone books). Lung cancer, where a medication occurs, was recognized for this move. This medicine was used, and the patient recovered. So businesses in the life sciences are beginning to handle their entire supply chain through data science approaches.
一个真实的例子是化疗失败的卵巢癌患者。 因此，为了鉴定导致癌症的错位核苷酸碱基，人们进行了基因组测序。 有人注意到大数据分析人员的30亿个基本对中的修改(这对应于7798年哈利·波特的《哲学家的石头》书中的单词数)。 此举认识到发生药物的肺癌。 使用了这种药，病人康复了。 因此，生命科学领域的企业开始通过数据科学方法来处理整个供应链。
Biomarker scanning science publication: On a regular basis, there are several hundreds of scientific papers on the identification of biomarkers by numerous research teams around the world for all various diseases. In order to discover new cures, it is important for life sciences companies to recognize the newly discovered biomarkers in order to incorporate them into their unique research fields. Work is hugely onerous and time-critical. They can prevent duplication in research by knowing the latest applicable research, and they can speed up the time to market.
生物标志物扫描科学出版物：全世界有许多研究团队定期针对有关各种疾病的生物标志物的鉴定发表数百篇科学论文。 为了发现新的治疗方法，生命科学公司必须认识到新发现的生物标志物，以便将其纳入其独特的研究领域，这一点很重要。 工作非常繁重且时间紧迫。 他们可以通过了解最新的适用研究来防止重复研究，并且可以加快产品上市时间。
The volume of information is so big that it’s not possible to do anything manually. So very sophisticated NLP algorithms that find the relevant publications are created. Apart from knowing the content where such biomarkers are important, a decision must be provided on the validity of the reported findings and how they integrate into the company’s research — a very complex job.
信息量如此之大，以至于无法手动执行任何操作。 因此，创建了找到相关出版物的非常复杂的NLP算法。 除了了解这些生物标志物重要的内容外，还必须决定所报告发现的有效性以及如何将其整合到公司的研究中-这是一项非常复杂的工作。
所需技能： (Skills needed:)
How To Learn Data Science by Self Study and For Free | how to learn data science from scratch 如何通过自学和免费学习数据科学如何从零开始学习数据科学The work usually includes a background in science as well as expertise in data science. The established expertise in dealing with data regarding health records is required for senior positions. For specialized subjects, companies with matching skills may be very picky. All experience from operating in a dynamic setting that is science or engineering is highly welcomed. Bioinformatics know-how is a plus. Particularly for people with a science background who want to enter the data science field, this industry gives plenty of opportunities.
吨他的工作通常包括在科学数据的科学背景和专业知识。 高级职位需要具备处理健康记录数据的专业知识。 对于专业科目，具有匹配技能的公司可能会非常挑剔。 非常欢迎您在科学或工程学的动态环境中进行操作而获得的所有经验。 具有生物信息学专业知识者优先。 尤其是对于具有科学背景的人想要进入数据科学领域，该行业提供了很多机会。
效用 (Utility)
Industry
行业
Utilities The utility sector offers basic public services such as water, electricity, or natural gas. They build, own, and operate the related infrastructure, such as hydroelectric generators, nuclear power plants, electricity grids, control stations, water distribution systems, etc. That defines delivery. On the other side of the equation is the market demand that has to be met, i.e., single individuals and corporates.
ütilities公用事业板块提供基本的公共服务，例如水，电，或天然气。 他们建立，拥有和运营相关的基础设施，例如水力发电机，核电站，电网，控制站，配水系统等。 另一方面，必须满足的市场需求是单身个人和公司。
The supply and demand relationships and maintenance of infrastructure are very complex, and today they are heavily technical and data-driven in real-time. The industry is increasingly moving into IoT devices and so-called smart metering, which tracks any energy or water usage in real-time and provides utilities and customers with accurate information. It’s seen as the first step towards smart grids.
供求关系和基础架构的维护非常复杂，如今，它们是由实时技术和数据驱动的。 该行业正越来越多地涉足物联网设备和所谓的智能计量，该技术可实时跟踪任何能源或水的使用情况，并为公用事业和客户提供准确的信息。 这被视为迈向智能电网的第一步。
This industry works in two extremes: on the one hand, they have to sustain properties for a lifetime of 35 years, such as generating plants for delivery systems of drinking water for up to 100 years. On the other hand, energy can not be stored, and it requires real-time management.
这个行业有两个极端：一方面，它们必须维持35年的使用寿命，例如为饮用水输送系统建造发电厂长达100年。 另一方面，能量无法存储，因此需要实时管理。
data science projects for beginners | The Projects You Should Do To Get A Data Science Job 面向初学者的数据科学项目| 获得数据科学工作应该做的项目Utilities are one of the sectors with the largest data volume, and so they face all the associated difficulties in order to utilize them. At present, the industry is also experiencing a technological revolution and is introducing more and more sensors and IoT devices, resulting in even more real-time data becoming available.
公用事业是数据量最大的行业之一，因此，为了利用它们，它们面临所有相关的困难。 当前，该行业也正在经历一场技术革命，并正在引入越来越多的传感器和物联网设备，从而导致更多的实时数据可用。
The pay is around 5–10 percent lower on average than in the tech industry, based on my experience.
根据我的经验，薪水平均比科技行业低约5-10％。
Their data science skills have been outsourced by several utilities. So look for specialized small and medium-sized consulting firms that represent the utility market solely.
他们的数据科学技能已由多家公用事业公司外包。 因此，寻找专门代表公用事业市场的专业中小型咨询公司。
抗衰退 (Anti-recession)
Yeah, there is a very recession-resistant sector. Water, electricity, and power are always needed, regardless of the state of the economy.
是的，有一个非常抗衰退的行业。 无论经济状况如何，始终需要水，电和电。
专案 (Projects)
There are many fields where data science is used in the utility room, from asset performance management, failure, and prediction of failure, to energy supply management and customer analytics.
Ť这里有许多的领域中的科学数据在杂物间使用，从资产绩效管理，故障以及故障的预测，能源供应管理和客户分析。
Detection of water leakage: Trillions of liters of drinking water are leaked out of the water supply system in Europe and the USA. Installing the water sensors to detect leakage is still at the outset. Manual pipe measurement and tapping are common but are applicable neither efficiently nor regionally. Thus, based on the flow measurements at specific locations and water usage data from the end-users, prediction models are set up to identify areas with possible water loss.
漏水检测：在欧洲和美国，数万升的饮用水从供水系统中漏出。 仍然需要安装水传感器以检测泄漏。 手动管道测量和开Kong是很普遍的，但是既不能有效地使用，也不能在局部使用。 因此，基于特定位置的流量测量值和最终用户的用水量数据，可以建立预测模型以识别可能出现水流失的区域。
Preventive power grid control with drones: In the US alone, power grids have a duration of 160,000 miles for high-voltage power lines and millions of miles for local low-voltage distribution lines. Monitoring all lines for potential threats such as, for example, trees that might damage a line is an almost impossible undertaking. Commercial drones are thus used to patrol the adjacent area along the lines and capture videos. For the automatic detection of possible threats, computer vision algorithms are generated or enhanced.
用无人机进行预防性电网控制：仅在美国，高压电网的电网持续时间为160,000英里，本地低压配电线的电网持续时间为数百万英里。 监视所有线路是否存在潜在威胁，例如可能损坏线路的树木，这几乎是不可能的任务。 商业无人机因此被用于沿线巡逻相邻区域并捕获视频。 为了自动检测可能的威胁，生成或增强了计算机视觉算法。
Consumption projections and competitive pricing: One of the most relevant statistics for maintaining the supply is the estimate of electricity consumption. Note, they can’t store electricity. So the supply must be assured in real-time. This is a very complex method, from controlling the generating capacity of hydroelectric generators to transmitting it via the power lines, buying and selling energy, and setting incentives for using less or more power with the corresponding pricing over particular time frames. Long-term and short-term conflicting impacts, different seasonalities, weather predictions, and short-term variations must be handled.
耗电量预测和有竞争力的价格：维持供电最相关的统计数据之一是耗电量的估算。 请注意，他们不能储电。 因此，必须实时保证供应。 这是一种非常复杂的方法，从控制水力发电机的发电量到通过电力线传输，买卖能源，以及设置激励措施以在特定时间范围内以相应的价格使用更少或更多的电力。 必须处理长期和短期的冲突影响，不同的季节，天气预报和短期变化。
With all the data volume and a short time to respond to the expected result, it is a very delicate problem and not easy to solve.
由于所有的数据量和响应时间都很短，因此这是一个非常棘手的问题，不容易解决。
需要技能 (Need skills)
The utility industry operates with several statistical models, mostly from Operations Analysis. Therefore the data scientist should be well established in mathematics and mathematical models. You should at least have basic knowledge of how the business operates and how a vast volume of data can be handled, even in real-time.
公用事业行业使用几种统计模型进行操作，其中大部分来自运营分析。 因此，数据科学家应在数学和数学模型方面建立良好的基础。 您至少应具备有关业务运作方式以及如何处理大量数据(即使是实时的)的基本知识。
食品饮料行业
产业领域 (Food and Drink Industry
Industries)
The food and beverage industry comprises a wide variety of businesses from restaurants, coffee shops, and fast-food chains, food, and beverage transportation providers, food producers, to giant multinationals such as Nestlé, PepsiCo, Anheuser-Busch InBev, JBS, etc.
食品和饮料行业包括餐馆，咖啡店和快餐连锁店，食品和饮料运输提供商，食品生产商，以及雀巢，百事可乐，百威英博，JBS等大型跨国公司。 。
My advice deals mainly with various international opportunities. They have different brands, practical food and beverages, and even pet food. Their business is based not only on customer behavior but also on all sellers’ conduct of their goods.
我的建议主要涉及各种国际机会。 他们有不同的品牌，实用的食品和饮料，甚至还有宠物食品。 他们的业务不仅基于客户的行为，而且还基于所有卖方对其商品的行为。
The multinationals’ wage standard is equivalent to the software industry. Area employers pay much smaller wages.
跨国公司的工资标准相当于软件行业。 区域雇主支付的工资要少得多。
抗衰退 (Anti-recession)
In part the industry is recession-proof. Both, soft drinks and alcoholic beverages like wines and spirituous beverages, see decreases during recessions. Big brewers, by comparison, face just a slight decline. During recessions, restaurant spending declines dramatically, while grocery store spending stays steady, and discount stores will boost their profits.
该行业在某种程度上是防衰退的。 软饮料和含酒精饮料(如葡萄酒和烈性饮料)在衰退期间都会减少。 相比之下，大型啤酒厂仅面临小幅下降。 在经济衰退期间，餐厅支出急剧下降，而杂货店支出保持稳定，而折扣店将提高利润。
AI VS ML VS DL VS Data Science | data science vs machine | Neuralink: Elon Musk’s entire brain chip AI VS ML VS DL VS数据科学| 数据科学与机器| Neuralink：Elon Musk的整个大脑芯片项目：(Projects:)
Sentiment analysis and identification of negative comments: Currently, concerns about a product are first made public on social media sites. Extreme cases such as food product contamination, for instance, are easily in the headlines. For large companies, tracking all of their product comments across the globe 24/7 in real-time is important. The brand needs to respond rapidly when an impactful statement is detected. It is important to evaluate the meaning of the possible incident and initiate subsequent behavior.
情绪分析和负面评论的识别：当前，有关产品的担忧首先在社交媒体网站上公开。 例如，食品污染等极端情况很容易成为头条新闻。 对于大型公司而言，实时跟踪全球24/7的所有产品评论非常重要。 检测到有影响力的陈述时，品牌需要Swift做出React。 重要的是评估可能发生的事件的含义并启动后续行为。
There is no need for action on many negative emotions. Incidents that need urgent intervention from the executive committee are on the other side of the scale. It is tricky to find the right combination in the algorithms for machine learning. It’s an extremely exciting area where misclassification is relevant.
无需对许多负面情绪采取行动。 需要执行委员会紧急干预的事件在规模的另一端。 在机器学习算法中找到正确的组合是很棘手的。 这是一个与分类错误有关的令人兴奋的领域。
On-time production and delivery: beverage producers for soft drinks need to prepare a demand for drinks, measure back their production schedule and capacities, and require their ingredients from their suppliers. In addition to seasonalities, variables such as weather, bigger and smaller events, market patterns, price wars, economic circumstances, purchasing power from buyers, manufacturing time and capacities, shelf life, etc., need to be considered. To ensure the delivery on time of the drinks to vendors or event catering, the logistics need to be coordinated in advance. Again it is a non-trivial job and demands of highly trained data science teams.
准时生产和交付：软性饮料的饮料生产商需要准备饮料需求，重新计算生产时间表和产能，并要求供应商提供其原料。 除了季节性之外，还需要考虑变量，例如天气，更大或更小的事件，市场格局，价格战，经济状况，购买者的购买力，制造时间和产能，保质期等。 为了确保将饮料按时交付给供应商或活动餐饮，需要提前协调物流。 同样，这是一项不平凡的工作，也是训练有素的数据科学团队的要求。
Quality assurance: The customer expects a product’s flavor, performance, quality, and shelf-life to be consistent over the year and irrespective of the position of consumption. Many factors influence the outcome of production, starting from the correct quantity of ingredients, their consistency, season, country of production and conditions of transport, storage, and conditions of production, such as temperature, strain, variations in production time, etc. It is a highly non-trivial data science challenge to find the right pattern of ingredients and production parameters per generated batch so that the result is always the same.
质量保证：客户希望产品的风味，性能，质量和保质期在一年中保持一致，而与消费位置无关。 从正确的配料数量，配料的稠度，季节，生产国家和运输条件，存储条件以及生产条件(例如温度，应变，生产时间的变化等)开始，许多因素都会影响生产结果。在每个生成的批次中找到正确的配料模式和生产参数模式，以使结果始终相同，是一项非常重要的数据科学挑战。
需要技能 (Need skills)
They expect in-depth knowledge of the data science approaches from regression to neural networks. Time series expertise is required when working on production issues, as well as NLP experience in the field of customer analytics.
他们期望对从回归到神经网络的数据科学方法有深入的了解。 处理生产问题时需要时间序列专业知识，以及客户分析领域的NLP经验。
商业商品
产业领域 (Commercial Goods
Industries)
Generally speaking, one might assume that this industry includes all of its production, manufacturing, machinery, and sales which are not sold directly to a customer. Subsectors include building, manufactured buildings, industrial machinery and tools, cement and metal processing, and industrial components. GE, Siemens, Hitachi, 3 M, Honeywell International, Bosch, Lockheed Martin, or ABB are examples of well-known multinational companies. These businesses have not only undergone their own complete digital transformation over the last few years and have fully automated development, but also have their own channels as a service to their customers and large data and technology teams.
一般而言，人们可能会认为该行业包括其未直接出售给客户的所有生产，制造，机械和销售。 子行业包括建筑物，工业建筑，工业机械和工具，水泥和金属加工以及工业组件。 GE，西门子，日立，3 M，霍尼韦尔国际，博世，洛克希德·马丁或ABB是著名的跨国公司的例子。 这些企业不仅在过去几年中经历了自己的完整数字化转型，并实现了完全自动化的发展，而且还拥有自己的渠道来为客户以及大数据和技术团队提供服务。
The industry has a distinction, the so-called “hidden champions.” A hidden champion is a business that is at the top of the world market but has sales of less than $5 billion, and in public it is almost unknown. Usually, these companies are high-tech businesses, thought leaders in digitalization and technology, and are usually based in nowhere. Its engine is Data and AI. It is a data scientist’s paradise. Finding such a secret champion and getting hired isn’t an easy task though.
该行业有一个区别，即所谓的“隐形冠军”。 一个隐藏的冠军是一家在世界市场上名列前茅，但销售额不到50亿美元的企业，在公众场合几乎是未知的。 通常，这些公司是高科技企业，是数字化和技术领域的思想领袖，并且通常不在任何地方。 它的引擎是数据和人工智能。 这是数据科学家的天堂。 找到这样一个秘密冠军并被录用并不是一件容易的事。
The amount of pay is similar to that of the tech industry. The benefits and working culture are above average particularly at secret champions, and the employee is still a valued human being and not a number.
薪酬金额与科技行业的金额相似。 员工的福利和工作文化高于平均水平，尤其是在秘密冠军上，而员工仍然是一个有价值的人，而不是一个数字。
耐衰退 (Recession-resistant)
The straightforward answer is: it depends. It is not possible to make a general statement because it depends on the sector and the type of recession. To offer you an example, fashion production collapsed in the current COVID-19 crisis, and with it, the market for industrial machinery in that sector. But one secret champion making sewing machines is unable to fulfill global demand. High-precision machines from the companies are versatile in the application and are now used for the production of masks. My remark is that a recession is less likely to strike secret champions.
直接的答案是：这取决于。 由于这取决于行业和经济衰退的类型，因此无法做出一般性声明。 举个例子，在当前的COVID-19危机中，时装生产崩溃，随之而来的是该部门的工业机械市场。 但是制造缝纫机的一个秘密冠军却无法满足全球需求。 这些公司提供的高精度机器用途广泛，现已用于生产口罩。 我的话是，衰退不会打击秘密冠军。
专案 (projects)
Sensors, connected devices, and automation that makeup intelligence machines, which generate a large amount of real-time data, are driving the industry and projects.
构成大量实时数据的化妆智能机的传感器，连接的设备和自动化技术正在推动行业和项目发展。
Safety of employees: Worker’s accidents are expensive, not just because of the accident itself but also because of the worker’s absence and reputational harm. Today, staff are more and more equipped with sensors, vibrators, or integrated cameras in the heavy equipment environment. So, one of these devices’ data is analyzed. The analysis of real-time data on trends that recognize a dangerous situation for the worker and contribute to an alarm, e.g. a high-pitched tone, is an example. Another example is trend recognition for unhealthy job actions such as erroneous ergonomic lifting and subsequent worker recommendations for change.
员工安全：工人事故的代价昂贵，不仅是因为事故本身，还因为工人的缺席和声誉受损。 如今，在重型设备环境中，员工越来越多地配备了传感器，振动器或集成摄像头。 因此，将分析这些设备的数据之一。 例如，对趋势的实时数据进行分析，这些趋势可识别出工人的危险状况并有助于发出警报，例如高音。 另一个例子是对不健康工作行为的趋势识别，例如错误的人体工程学举动以及随后的工作人员变更建议。
Optimization of productivity: We have all learned regarding predictive maintenance. The time points of system failure are estimated using machine learning techniques, and the expected maintenance. Today, leading organizations can now detect minor anomalies a few weeks in advance before a malfunction occurs. This provides not only time for planned maintenance, but also to optimize the entire production over that span, including how the expected failure can eventually be prevented by changing production parameters. There are high-dimensional issues to solve that include method on the machine learning frontier.
优化生产力：我们都了解了预测性维护。 使用机器学习技术和预期的维护来估计系统故障的时间点。 如今，领先的组织现在可以在故障发生前几周就检测出较小的异常。 这不仅提供了计划内维护的时间，而且还优化了该范围内的整个生产，包括如何通过更改生产参数最终防止预期的故障。 有很多高维度的问题需要解决，其中包括机器学习领域的方法。
Research and Development (R&D): Intelligent machines need to perform their tasks with intelligent and robust algorithms. Diagnostic machines are an example where a camera is mounted to track the control panel, i.e. how the staff and their hand movements use it. These data are combined with data about system performance and failure. The self-adjusting processes are implemented into the computer based on the patterns to ensure consistent work efficiency.
研究与开发(R＆D)：智能机器需要使用智能且强大的算法来执行其任务。 诊断机器是一个示例，其中安装了摄像头以跟踪控制面板，例如，员工及其手部动作如何使用它。 这些数据与有关系统性能和故障的数据结合在一起。 根据模式将自我调整过程实施到计算机中，以确保一致的工作效率。
需要技能 (Need skills)
They are searching for highly qualified data scientists with experience of both advanced and engineering approaches. Experience is important in the handling of high volume and real-time data. Equally relevant is the attitude for working in a team and smaller businesses.
他们正在寻找具有先进和工程方法经验的高素质数据科学家。 经验对于处理大量实时数据非常重要。 同样重要的是在团队和小型企业中工作的态度。
农业产业 (Agricultural Industry)
Industry
行业
Industry includes animals, aquaculture, i.e. fisheries, crops and plants, and forestry in research, art, and industry. Usually, we are most acquainted with agriculture. Farming also turns into a company that is powered by technology. Agriculture needs to produce more and more goods and food, with fewer resources. Technological progress includes autonomous tractors and equipment, digitized disease identification and pest control, improved weather forecasts, automatic irrigation and harvesting systems, and, to name a few, livestock health systems. That can only happen with massive quantities of data and a lot of clever algorithms.
工业包括动物，水产养殖，即渔业，农作物和植物，以及研究，艺术和工业中的林业。 通常，我们最了解农业。 农业也变成了一家以技术为动力的公司。 农业需要用更少的资源生产越来越多的商品和粮食。 技术进步包括自动拖拉机和设备，数字化疾病识别和病虫害控制，改进的天气预报，自动灌溉和收割系统，以及牲畜保健系统。 只有大量的数据和许多聪明的算法才能实现。
Fast analytics on Glassdoor provides an average age range of around 10 percent less than an almost equivalent role in a software company. But one has to understand the location variations, as there are not many agricultural data science jobs in the major centers where tech firms are focused.
Glassdoor上的快速分析提供的平均年龄范围比软件公司中几乎相同的角色低大约10％。 但是，人们必须了解地理位置的变化，因为在主要集中技术公司的主要中心中，农业数据科学工作并不多。
抗衰退 (Anti-recession)
This is a mixed blessing to the industry. Agriculture is mostly a low-margin sector, and any cut in food spending during a recession has a direct effect on the income of the farmers. On the other hand, more digitalization leads to more successful and productive digitalization. So, we usually do not see a lot of improvement on the innovation side there, and it can be considered very recession-resistant.
这对业界来说是好事。 农业主要是低利润部门，经济衰退期间任何粮食支出的削减都会直接影响农民的收入。 另一方面，更多的数字化将导致更多的成功和富有成效的数字化。 因此，我们通常不会在创新方面看到很多改进，并且可以认为它非常抗衰退。
专案 (Projects)
The key-word is precision farming. Based on real-time data on crops, plants, soil, hyper-local weather, temperature, humidity, field sensors, satellite, and drone images, it is possible to evaluate the needs of individual plants and decide the necessary treatment.
关键字是精准农业。 基于有关作物，植物，土壤，超局部天气，温度，湿度，田间传感器，卫星和无人机图像的实时数据，可以评估单个植物的需求并决定必要的处理方法。
Cow health: temperature-measuring earmarks, cow fitness trackers, GPS neckbands, and even stomach sensors are the accessories available for cows today. These data in real-time are then analyzed using machine learning algorithms to identify abnormalities in the health of the individual cow, and a corresponding warning is then sent either to the farmer or directly to the veterinarian. The development of such algorithms is difficult because too many warnings or incorrect warnings would lead to incorrect treatments, and no warning would lead to no care in a serious health situation.
奶牛健康：今天，奶牛可以使用测量温度的专用标记，奶牛健身追踪器，GPS颈带甚至胃部传感器。 然后使用机器学习算法对这些数据进行实时分析，以识别单个母牛的健康状况是否异常，然后将相应的警告发送给农场主或直接发送给兽医。 由于过多的警告或不正确的警告将导致错误的治疗，并且在严重的健康状况下没有警告将导致无法护理，因此此类算法的开发非常困难。
Disease detection and management: Microscopic diseases may be identified with computer vision, either with field images or infrared images. The spread of a disease can be predicted in conjunction with additional local data such as weather, or soil parameters. The correct treatment for precisely the polluted area is calculated based on all of these results. And it should ensure that there is neither too much nor too little use of pesticides. Here you function on the image recognition frontier techniques.
疾病检测和管理：微观疾病可以通过计算机视觉，野外图像或红外图像进行识别。 可以结合其他本地数据(例如天气或土壤参数)来预测疾病的传播。 根据所有这些结果，计算出精确处理污染区域的正确方法。 并且应该确保既不使用过多农药，也不使用过多农药。 在这里，您可以使用图像识别前沿技术。
Harvesting and grading: There are now automated harvesting devices that automatically grade fruits or vegetables, too. Tomatoes are one example. They are also grown in robot greenhouses. These robots not only handle data-driven cultivation but also harvest and rate the ripe fruits into the various grades. Again, this is an intensive work of very machine learning where you can use all the advanced neural network models.
收割和分级：现在有自动收割设备，也可以对水果或蔬菜进行自动分级。 西红柿就是一个例子。 它们还生长在机器人温室中。 这些机器人不仅处理数据驱动的栽培，而且还收获成熟的果实并将其分级为不同等级。 同样，这是非常机器学习的密集工作，您可以在其中使用所有高级神经网络模型。
必备技能 (Required Skills)
The positive message is that you should not want the agricultural sector to have sufficient education. They are pursuing open and curious data scientists to extend the applications of data science and AI into sectors that are less considered. But don’t underestimate the ripeness of the methods used. For very specialized systems, be prepared.
积极的信息是您不希望农业部门接受足够的教育。 他们正在追求开放和好奇的数据科学家，以将数据科学和AI的应用扩展到未被考虑的领域。 但是不要低估所使用方法的成熟度。 对于非常专业的系统，请做好准备。
连接到所有人 (Connecting to All)
Outside of the software industry, several exciting industries provide interesting opportunities to gain skills and knowledge that you otherwise could not encounter. Technology penetrates all industries and sectors, thus producing huge volumes of data. All businesses must become data-driven.
在软件行业之外，一些激动人心的行业提供了有趣的机会来获得您以前无法遇到的技能和知识。 技术渗透到所有行业和领域，从而产生大量数据。 所有业务都必须成为数据驱动的。
My advice to you is to be open-minded and think outside of the box while you are looking for a career in data science. It will give you a competitive edge in your career in data science.
我对您的建议是开阔胸怀，在寻找数据科学职业时跳出思维。 这将使您在数据科学事业中具有竞争优势。
Bio: Shaik Sameeruddin I help businesses drive growth using Analytics & Data Science | Public speaker | Uplifting students in the field of tech and personal growth | Pursuing b-tech 3rd year in Computer Science and Engineering(Specialisation in Data Analytics) from “VELLORE INSTITUTE OF TECHNOLOGY(V.I.T)”
简历： Shaik Sameeruddin我使用分析和数据科学帮助企业推动增长| 公开演讲者| 提升技术和个人成长领域的学生| 从“ VELLORE TECHNOLOGY OF TECHNOLOGY(VIT)”获得计算机科学与工程专业(数据分析专业)第三年学士学位
数据科学与人工智能以及国家和国际实习的职业指南和路线图，请参考：(Career Guide and roadmap for Data Science and Artificial Intelligence &and National & International Internship’s, please refer :)
翻译自: https://medium.com/@shaikSameeruddin/top-exciting-markets-outside-of-software-firms-for-a-data-scientist-and-a-i-career-c7a35e1de0e1