Create An Effective Data Scientist Onboarding Plan Like a Pro (Template Included)
In an increasingly data-driven economy, data scientists are crucial to a company's survival and expansion.
Data scientists (or data analysts and engineers) have versatile skills that cover coding, product development, and reporting and analysis.
The complexity of data scientist roles can explain why these employees need a more intensive onboarding process, as each company has its systems, tools, and programming language.
In the era of "the Great Resignation," you definitely wouldn't want your newly hired data analysts to feel overwhelmed when they first set foot into your workplace.
But are you struggling to put together the pieces of an effective and rewarding onboarding process for your data scients?
Worry no more.
We'll walk you through data scientist onboarding and why it's so important. Plus, we've included a data scientist onboarding template to help you get started.
✈️ Why is onboarding important for data scientists?
Onboarding new employees efficiently is vital to their long-term satisfaction.
If their first three months are chaotic, it doesn't give a good impression of their future in the firm.
For Lisa Cohen, Data Science Team Lead at Microsoft Customer Growth Analytics, the onboarding period is critical not just for the new data scientist but also for their manager:
"In a number of ways, a new hire's first day is — so far — probably the crowning achievement of their career. A new hire is at their most vulnerable during those first few days and weeks. Now is your best chance to demonstrate empathy for their situation and to foster a relationship of trust."
One way managers can establish trust is by ensuring role clarity. There are many components in data scientists' roles, so role clarity is a must for any new hire. For example, they can work with product development one minute and the engineering team the next.
Without a clear division of responsibilities, data analysts can get burned out quickly.
Data scientists also need the onboarding period to get familiarized with the company's field of expertise. You also need to introduce them to your firm's processes, systems, and tools.
For example, what are the programming skills and languages utilized (e.g., SQL, Python), and how will they be trained for software they're unfamiliar with?
Tip: Remember that the onboarding process should always prioritize employee experience. Your new hires' productivity and professional relationships depend on how rewarding their onboarding experience is.
📝 Data scientist onboarding 30-60-90 day plan template
A 30-60-90 day plan ensures your data scientists’ first three months go smoothly.
Tip #1: Using a standardized plan helps People Ops and Managers create a consistent experience for future hires.
Tip #2: However, customizing your employee onboarding template based on specific roles/teams/departments is essential.
Below is a data scientist onboarding 30-60-90 day checklist to help you get started.
Preparation and preboarding: Day 0
This stage is crucial as it sets the environment and vibe for the new hires. So don't skip this one!
- Send out necessary onboarding documents to be signed, company policies, and handbook.
- Prepare accounts and access rights, particularly to the firm's statistical and analytics tools.
- Notify colleagues and book onboarding meetings.
- Send a welcome email and package. These are the small gestures that make a big difference.
- Plan out the first week of orientation and a rough draft of the 30-60-90-day plan. Ensure that all key stakeholders contribute to setting priorities and goals, such as team leader, mentor, department manager, etc.
The first 30 days: Focus on compliance and clarity
The first month on the job is all about getting to know the company's business goals, clients, and technology stack or systems.
Tip: You can also use this period to encourage networking.
Day 1: Provide a worthy reception
- Celebrate with a team intro message. Here's a team introduction sample.
- Say hi in person (or on a call).
- Host a (virtual) lunch.
- Hand out the access card/ID/key, hardware, and other tools.
- Introduce new hires to their onboarding buddy or mentor.
Week 1: Get new employees on track
- Have them sign off compliance policies.
- Introduce them to company goals and projects, including datasets and fields of expertise.
- Carry the first 1:1 conversations focusing on role clarity and setting expectations.
- Finalize the 30-60-90-day plan, including suggesting day-to-day resources like internal chat rooms and communication portals.
- Create an initial assignment and encourage to start gathering domain knowledge.
- Celebrate the first week with a small message.
First 30 days
- Introduce team and collaborators from other departments (e.g., product managers, engineering division).
- Ensure data analysts attend all relevant meetings, particularly among teams like Product and Marketing.
- Deliver regular day-to-day tips, such as bite-sized messages via Slack, Teams, or mail, to deliver useful just-in-time info. This will facilitate learning in the flow of work.
- Start setting goals and onboarding metrics for success.
A key goal is to develop a deeper understanding of programming tools and data analysis software. An additional goal is to go through the main datasets.
- Start providing new employee feedback. Schedule regular feedback meetings.
- Ask for onboarding feedback as well. Onboarding surveys are an excellent method you can use.
- Ensure that new hires have regular check-ins with their onboarding buddy. You can also collect insights through a buddy survey to improve your process for future hires.
Days 30-60: Focus on training
After the first month, your data scientist should be able to work more independently and start to explore other tasks.
The manager will still provide regular feedback to help them reach their goals. Still, in the second month, it's time for data analysts to have a more hands-on exposure to their tools and processes.
- Identify potential internal and external training resources (e.g., video recordings and workshops).
- Choose a senior data scientist or two to shadow during the month.
- Start attending some hands-on training.
- Learn about past projects and initiatives, particularly the challenges.
➡️ Check out our in-depth information on the best practices for training new employees.
A key goal at this stage is to discover and understand the customers/stakeholders and their data needs.
- As feedback starts coming in, encourage your new hires to engage in self-reflection exercises. It's an effective way to get them in sync with your workplace's feedback culture.
- Don't forget about culture and social acclimation. So, schedule coffee dates and onboarding buddy check-ins.
Activities for the 60-day milestone
- Reflect on 60-day goals. What went well? What did not go as expected?
- Set goals for the next 30 days.
- Address any significant areas of concern or improvement.
- Prepare your new data analyst to participate in a live project.
Days 60-90: Focus on accountability and role proficiency
In the last onboarding phase, your new joiners take on even more autonomy. They should take full responsibility for their work while also being proactive in improving the team, process, or company.
You can decide whether day 90 will end your formal onboarding. From there, you transition your new data scientist into ongoing training and development to get them ready for continued success in their role.
Main objectives for this period
- Troubleshoot issues independently.
- Contribute to brainstorming or process improvements.
- Participate in live projects by starting small, like follow-up analysis or stakeholder inquiry.
Day 90 milestone activities
- Assess onboarding goals and onboarding metrics.
- Look at the big picture of performance so far.
- Identify and discuss any areas of concern and interest.
- Set new goals for the next 6-months. Consider also adding goals to reach until concluding the first year in your organization.
➡️ If you need other templates, we have you covered. Check out our free and essential onboarding templates.
👀 What does an effective data scientist onboarding process look like?
Generally, onboarding has four major phases: preboarding, orientation, role-specific training, and ongoing development.
In particular, role-specific training is where things become intensive for your new data analysts.
Preboarding is the time to consider how to ease them into the roles.
Tip #1: As you are preparing the first draft of their onboarding plan, consider the following questions:
What kinds of projects should they handle first?
How do their roles and expertise fit into the overall business goals?
Tip #2: Enlist your main stakeholders to find the answers to these questions.
Tip #3: Make sure you document all details. You can include all elements in the onboarding checklist or use an onboarding portal.
According to Danny Malter, a former Data Science Manager at MillerCoors and Hyatt Hotels Corporation, it's best for new analysts to start small:
"Anybody starting on a data analytics or data science team, it's really important that they spend probably a good week, if not more, just going through the data."
For example, they can clean up data 80% of the time and only do actual analysis for the remaining 20%
During the first crucial months of onboarding, managers should ensure their data scientists get a comprehensive walkthrough of the datasets and statistical programs, particularly the ones they're unfamiliar with.
Tip #4: The analysts should know the teams they will work closely with daily.
For example, some data science teams collaborate almost exclusively with marketing in driving sales outreach and strategy. Others function like research and development groups, independently generating and testing data.
Tip #5: The critical thing to remember is to keep the new data scientists engaged every step of their onboarding journey. When they know exactly how they contribute to the company's success, they are more likely to be motivated.
➡️ Discover 11 ways to engage new employees starting from day one.
⚙️ 3 Reasons why you need to automate your data scientist onboarding process
The greatest benefit of an automated onboarding process is that it saves time.
➡️ Storyblok, for example, saves 15+ hours every week while taking their remote onboarding experience to the next level.
Because the process follows customized journeys or workflows, new joiners have a clear map to follow.
"What surprised me most was that you can automate so much without sacrificing experience. We are sending people trackable tasks, engaging content, fun reminders via Slack, and connecting them to their onboarding buddies. All with a single click." Markus Schwarz, People Experience Manager at Storyblok.
Tip: Don't forget that you can also quickly start onboarding before Day 1 with an automated preboarding workflow.
➡️ Access our preboarding template to help you get started.
Enhanced new hire experiences
Structured journeys create better experiences for new data analysts.
When your onboarding touches on the 5 Cs of onboarding, compliance, clarification, confidence, connection, and culture, your employees will feel genuinely welcomed into your organization.
Tip: Positive experiences are great for your employer branding. But that's not the sole benefit.
Increased productivity and motivation
Positive onboarding experiences result in increased productivity and motivation.
➡️ You don't have to take our word for it. Check out how Zavvy helped Alasco cut time-to-productivity in half with a structured and fun onboarding process.
Tip: Automation avoids unpleasant surprises or misaligned expectations.
Instead of feeling nervous and confused about navigating their new roles, your data scientists will feel empowered when they know exactly how to progress and meet expectations.
➡️ Set up your new data scientist for success with Zavvy
Offer proper guidance to your new data analysts by automating your onboarding workflows.
You can create a detailed plan that can inform and engage through employee onboarding software.
Plus, through our preboarding software, you can set up a welcoming environment that can soothe first-day jitters.
With Zavvy's onboarding template gallery, you get a jump start to structured, enlighting, and fun onboarding plans.
And, to cap it all off, you'll be able to track new hire progress, automatically schedule events and send onboarding journeys, and include interactive features.
Once onboarding ends, Zavvy helps you smoothly transition into long-term training and development plans and feedback cycles for your data science team.
Book a demo to discover how our automated workflows can take your employee experience to the next level.