Data Scientist
TradeJobsWorkforce90081 Los Angeles, CA, USFull-time
Data Scientist Job Duties: Formulates and leads guided, multifaceted analytic studies again... Show more
Junior Data Scientist/Data Engineer/AISynergisticIT • Los Angeles, CA, US
Junior Data Scientist/Data Engineer/AI
SynergisticIT • Los Angeles, CA, US
30+ days ago
Job type
- Full-time
Job description
Build the Data Backbone That AI Runs On
For jobseekers who learned analytics/SQL but want Data Engineering + ML readiness
If you've been learning SQL, dashboards, or basic Python and still feel stuck, you're not imagining it—the hiring market has shifted. Companies don't just want "someone who can analyze data.” They want professionals who can move data, clean it, structure it, and deliver it reliably so analytics teams and AI systems can actually use it. That's why Data Engineering and ML/AI-ready skills are among the most valuable career paths today. The real secret? AI doesn't replace data engineering—it depends on it. Every machine learning model, forecasting pipeline, and analytics dashboard is only as strong as the pipelines behind it.
That's where SynergisticIT's Job Placement Program (JOPP) comes in. Since 2010, SynergisticIT has helped candidates land full-time roles with many leading companies, and SynergisticIT's JOPP is designed to close the gap between what you've learned and what employers are hiring for right now. If you're tired of taking course after course without seeing hiring results, you're exactly the type of candidate JOPP was built for. In fact, around 30% of JOPP candidates have already tried other bootcamps, university bootcamps, Udemy, or Coursera—and still didn't get hired because most programs focus on content completion, not job outcomes.
Here's what changes when you follow a placement-first approach: instead of collecting certificates, you build a hire-ready profile—projects that mirror real pipelines, interview preparation that matches what hiring managers ask, and a structured job search system that includes candidate marketing and interview scheduling. SynergisticIT works with candidates across multiple job paths, including entry-level software programmers, Java full stack developers, Python/Java developers, Data Analysts, Data Engineers, Data Scientists, and Machine Learning Engineers. The focus areas include Java / Full Stack / DevOps and Data roles such as Data Engineering, Data Analytics, BI, ML/AI, because those are the tracks that consistently show demand across industries.
If you're targeting Data Engineering specifically, the competitive edge comes from mastering the "full pipeline” toolkit: SQL for querying, Python for data processing, data modeling for clarity, ETL/ELT patterns for reliability, cloud for scalability, and orchestration for automation. Employers increasingly want candidates who can demonstrate they understand how real companies operate: data quality checks, incremental loads, pipeline monitoring, governance basics, and performance tuning—not just a one-time notebook demo.
SynergisticIT's approach also recognizes a practical truth: many jobseekers are capable, but they're not getting traction because of missing links—project depth, interview performance, and lack of structured support. That's why JOPP emphasizes not only learning, but becoming job-ready. It's the difference between "I took a course” and "I can build a pipeline, explain it, defend design choices, and deploy it.”
Ideal candidates for this path often include:
If you want to explore the program directly, here are the key links:
Contact SynergisticIT:
Because in tech, it's not only what you know—it's how you build, how you present it, and who guides you through the hiring process.
Build the Data Backbone That AI Runs On
For jobseekers who learned analytics/SQL but want Data Engineering + ML readiness
If you've been learning SQL, dashboards, or basic Python and still feel stuck, you're not imagining it—the hiring market has shifted. Companies don't just want "someone who can analyze data.” They want professionals who can move data, clean it, structure it, and deliver it reliably so analytics teams and AI systems can actually use it. That's why Data Engineering and ML/AI-ready skills are among the most valuable career paths today. The real secret? AI doesn't replace data engineering—it depends on it. Every machine learning model, forecasting pipeline, and analytics dashboard is only as strong as the pipelines behind it.
That's where SynergisticIT's Job Placement Program (JOPP) comes in. Since 2010, SynergisticIT has helped candidates land full-time roles with many leading companies, and SynergisticIT's JOPP is designed to close the gap between what you've learned and what employers are hiring for right now. If you're tired of taking course after course without seeing hiring results, you're exactly the type of candidate JOPP was built for. In fact, around 30% of JOPP candidates have already tried other bootcamps, university bootcamps, Udemy, or Coursera—and still didn't get hired because most programs focus on content completion, not job outcomes.
Here's what changes when you follow a placement-first approach: instead of collecting certificates, you build a hire-ready profile—projects that mirror real pipelines, interview preparation that matches what hiring managers ask, and a structured job search system that includes candidate marketing and interview scheduling. SynergisticIT works with candidates across multiple job paths, including entry-level software programmers, Java full stack developers, Python/Java developers, Data Analysts, Data Engineers, Data Scientists, and Machine Learning Engineers. The focus areas include Java / Full Stack / DevOps and Data roles such as Data Engineering, Data Analytics, BI, ML/AI, because those are the tracks that consistently show demand across industries.
If you're targeting Data Engineering specifically, the competitive edge comes from mastering the "full pipeline” toolkit: SQL for querying, Python for data processing, data modeling for clarity, ETL/ELT patterns for reliability, cloud for scalability, and orchestration for automation. Employers increasingly want candidates who can demonstrate they understand how real companies operate: data quality checks, incremental loads, pipeline monitoring, governance basics, and performance tuning—not just a one-time notebook demo.
SynergisticIT's approach also recognizes a practical truth: many jobseekers are capable, but they're not getting traction because of missing links—project depth, interview performance, and lack of structured support. That's why JOPP emphasizes not only learning, but becoming job-ready. It's the difference between "I took a course” and "I can build a pipeline, explain it, defend design choices, and deploy it.”
Ideal candidates for this path often include:
- Recent grads in CS, Engineering, Math, or Statistics with limited experience
- Jobseekers impacted by layoffs who want a more in-demand stack
- Professionals switching from non-tech or semi-tech roles into data/engineering
- Candidates with career gaps who need help rebuilding momentum
- CS grads who studied theory but lack projects and interview readiness
- Candidates applying repeatedly but not getting responses or interviews
- F1/OPT candidates who need structured outcomes and timely placement support
If you want to explore the program directly, here are the key links:
- Job Placement Program (JOPP):
- Java Job Placement Program:
- Data Science / Data Jobs Program:
- Event videos (OCW, JavaOne, Gartner):
- USA Today feature:
Contact SynergisticIT:
Because in tech, it's not only what you know—it's how you build, how you present it, and who guides you through the hiring process.
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Junior Data Scientist/Data Engineer/AI • Los Angeles, CA, US
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