Entry level java programmer with NLP Deep learning/(Remote)Since 2010 SynergisticIT has helped Jobse
SynergisticITChicago, IL
Other
Posted 12 days ago
Job description
The Tech Job market has been affected by massive layoffs and since 2021 there have been more than 600,000.00 tech layoffs.
The Job market is Hyper Competitive. For 1 position 500-1000 candidates or more are applying and laid off job seekers are also competing for entry level Job positions.
Please see the below links to know more about Synergisticit and some useful tips
Synergisticit Pics /Salaries of Successful Candidates
Synergisticit at Oracle Cloudworld 2023
Synergisticit at Gartner Data & Analytics summit
Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT
Technical Skills or Experience? | Which one is important to get a Job? | SynergisticIT
We regularly interact with the Top Tech companies to give our candidates a competitive advantage.
We at Synergisticit understand the problem of the mismatch between employer's requirements and Employee skills and that's why since 2010 we have helped 1000's of candidates get jobs at technology clients like apple, google, Paypal, western union, Client, visa, walmart labs etc to name a few.
We are continuously looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Data Engineers, Machine Learning engineers for full time positions with clients.
Who Should Apply? Recent Computer science/Engineering /Mathematics/Statistics or Science Graduates or People looking to switch careers or who have had gaps in employment and looking to make their careers in the Tech Industry.
We need Data Science/Machine learning/Data Analyst and Java Full stack candidates
Preferred SKILLS For Java /Full stack/Devops Positions
Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
Knowledge of Core Java , javascript , C++ or software programming
Spring boot, Microservices, Docker, Jenkins, Github, Kubernates and REST API's experience
For data Science/Data Analyst/AI/Machine learning Positions
Preferred SKILLS
Associate or Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT, Statistics, Mathematics or having good logical aptitude
Knowledge of Statistics, Gen AI, LLM, Sagemaker, Python, Computer Vision, data visualization tools
Candidates lacking technical skills can research our other programs which can assist in landing a Job
If you get emails from our Job Placement team and are not interested please email them or ask them to take you off their distribution list and make you unavailable as they share the same database with the client servicing team who only connect with candidates who are matching client requirements.
No phone calls please. Shortlisted candidates would be reached out. No third party or agency candidates or c2c candidates
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Scientist?
A: To succeed as a Data Scientist, one must possess core technical skills such as proficiency in programming languages like Python, R, or SQL, as well as expertise in machine learning algorithms, data visualization tools like Tableau or Power BI, and statistical modeling techniques. Additionally, strong soft skills like effective communication, collaboration, and problem-solving abilities, along with traits like curiosity, adaptability, and attention to detail, are crucial for success in this role. By combining these technical and soft skills, Data Scientists can effectively extract insights from complex data, drive business decisions, and drive career growth through continuous learning and innovation.
Q: What is the career path for a Data Scientist?
A: A Data Scientist's typical career progression involves starting as a Junior Data Analyst or Data Scientist, where they develop foundational skills in data analysis, machine learning, and visualization. As they gain experience, they can move into mid-level roles such as Senior Data Scientist or Lead Data Analyst, where they take on more complex projects, mentor junior team members, and contribute to strategic decision-making. Ultimately, senior Data Scientists can transition into leadership positions like Director of Data Science or Chief Data Officer, or pursue specialized roles like Data Engineering or Artificial Intelligence Research Scientist, depending on their interests and skills.
